Artículos de revistas sobre el tema "Non-parametric efficiency model"
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Thi Vu, Loan, Nga Thu Nguyen y Linh Hong Dinh. "Measuring banking efficiency in Vietnam: parametric and non-parametric methods". Banks and Bank Systems 14, n.º 1 (8 de febrero de 2019): 55–64. http://dx.doi.org/10.21511/bbs.14(1).2019.06.
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The article aims to evaluate the business efficiency of commercial banks in Vietnam using both parametric and non-parametric approaches. In this study, the Stochastic Frontier Analysis (SFA), which belongs to a parametric method, and Data Envelopment Analysis (DEA), a non-parametric approach, are applied to a sample of 30 joint stock commercial banks in Vietnam in the period of 2011–2015. Applying Tobit regression model, the impact of bank size, bank age, and the ownership feature on the efficiency of bank service industry in Vietnam is also investigated. The analysis results show that in general, the Vietnamese banking efficiency is improving during the selected period regardless of techniques used. However, there is small level of similarity in efficiency rankings identified from the SFA and DEA models. In terms of efficiency determinants, the results show that all three variables of size, age, and state ownership have a positive impact on bank efficiency.
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Murillo, Kelly Patricia. "A non-parametric dynamic model for measuring efficiency". Selecciones Matemáticas 10, n.º 02 (30 de noviembre de 2023): 324–32. http://dx.doi.org/10.17268/sel.mat.2023.02.08.
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Conventional efficiency evaluation systems present little diversity in the type of variables considered. This aspect generally leads to errors in the application of the models and in the corresponding interpretation of results. This study proposes a dynamic model to measure the efficiency of decision-making units, based on non-parametric Multidirectional Efficiency Analysis (MEA). The model presented here considers a complete structure, which includes intertemporal variables (desirable/undesirable intermediate inputs and outputs), discretionary/non-discretionary inputs; desirable/undesirable inputs and outputs. Dynamic score is defined first in a particular version and then in a more general version, considering two optimization problems. The directional contribution of each variable is examined, showing excess inputs and deficit outputs. In addition, a dynamic inefficiency index to measure the number of times each input was used inefficiently, is presented for both desirable and undesirable cases.
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Matulova, Marketa y Jana Rejentova. "Efficiency of European Airports: Parametric Versus Non-parametric Approach". Croatian Operational Research Review 12, n.º 1 (2021): 1–14. http://dx.doi.org/10.17535/crorr.2021.0001.
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This paper presents a performance evaluation of European airports, based on the application of both parametric and non-parametric approaches. We have evaluated the 115 busiest airports in Europe according to the number of passengers checked-in in 2018. The four inputs we used were the number of Terminals, Runways, Boarding gates, and Aircraft stands. Three variables were used to describe the outputs, namely, Passengers, Movements, and Cargo. The parametric method we chose to apply was the Stochastic Frontier Analysis (SFA) with the Cobb-Douglas production function, the Half-Normal distribution of inefficiency component, and the Normal distribution of an error term. As a basic SFA model only allows for a single output, we employed different methods to get a single efficiency score for each and every airport. Next, we evaluated the airport performance non-parametrically using several Data Envelope Analysis (DEA) models including the super-efficiency model. We compared the results obtained by individual approaches and discussed their pros and cons. Finally, we applied the program evaluation procedure to explore the effect of the different forms of airports ownership on their performance.
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Wang, Shouhong. "Adaptive non-parametric efficiency frontier analysis: a neural-network-based model". Computers & Operations Research 30, n.º 2 (febrero de 2003): 279–95. http://dx.doi.org/10.1016/s0305-0548(01)00095-8.
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Stavárek, Daniel y Iveta Řepková. "Efficiency in the Czech banking industry: A non-parametric approach". Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 60, n.º 2 (2012): 357–66. http://dx.doi.org/10.11118/actaun201260020357.
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This paper estimates the efficiency of the Czech commercial banks in the period 2001–2010 using the non-parametric Data Envelopment Analysis. We simultaneously use two alternative specifications – CCR model and BCR model – that differ in returns to scale assumption. Differences in estimated efficiency scores of individual banks are quite large up to 70 percentage points. Largest banks perform significantly worse than mid-size and small banks. This efficiency gap decreases if variable returns to scale are considered in the estimation. The average efficiency in the banking sector remained nearly unchanged during the analysed period. Although each year is estimated separately one can observe a deterioration of average efficiency during the recent crisis period.
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Wang, Yue, Valerie M. LeMay y Peter L. Marshall. "Relative efficiency and reliability of parametric and nonparametric sequential accuracy testing plans". Canadian Journal of Forest Research 26, n.º 10 (1 de octubre de 1996): 1724–30. http://dx.doi.org/10.1139/x26-196.
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The relative efficiency and reliability of parametric and nonparametric sequential accuracy testing plans were investigated using Monte Carlo techniques with normal and non-normal distribution generators. For the normal distributions, zero (no equation bias) and nonzero (some equation bias) means were simulated. For normal distributions with a nonzero mean, a modified nonparametric testing plan was developed and compared with the bias-free parametric test. The parametric testing plans resulted in average sample numbers to reach a terminal decision that were 20–40% smaller than the nonparametric testing plans, when the prediction errors of a model were normally distributed. In this circumstance, both the parametric and nonparametric testing plans yielded actual probabilities of making a type I or II error close to the nominal values, with the parametric testing plans giving somewhat lower error probabilities. When model errors followed a non-normal distribution, the nonparametric testing plans still resulted in error probabilities close to the nominal values, but this was not the case for the parametric testing plans.
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Pool, Sandra, Marc Vis y Jan Seibert. "Evaluating model performance: towards a non-parametric variant of the Kling-Gupta efficiency". Hydrological Sciences Journal 63, n.º 13-14 (26 de octubre de 2018): 1941–53. http://dx.doi.org/10.1080/02626667.2018.1552002.
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Hlali, Arbia. "Efficiency Analysis with non parametric method: Illustration of the Tunisian ports". Logistics & Sustainable Transport 9, n.º 1 (1 de febrero de 2018): 51–58. http://dx.doi.org/10.2478/jlst-2018-0005.
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AbstractThis paper applies a non-parametric method to provide level technical efficiency for 7 Tunisian ports during 18 years (1998-2015). These ports represent different data set. The use of the model of variable returns to scale (VRS) has led to interesting results. The results show that the most ports are characterized by low levels of technical efficiency, with the exception port of Rades. In addition, the result shows the variation of variable returns to scale and constant returns to scale of technical port’s efficiency. Furthermore, we concluded that the panel data improves the efficiency estimates.
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Koldanov, Petr y Vladimir Koldanov. "Nonparametric procedure for comparing the performance of divisions of a network organization". Business Informatics 18, n.º 1 (31 de marzo de 2024): 52–64. http://dx.doi.org/10.17323/2587-814x.2024.1.52.64.
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To solve the problem of comparative efficiency analysis of branch operations for a small volume of randomly observed data, a non-parametric approach is relevant, since it does not require a probabilistic model of observations. Comparing the results of the non-parametric approach with the results obtained within the traditionally used Gaussian model is also relevant. Additionally, obtaining a consistent comparison of a group (of no less than three) branches is important. Currently, the non-parametric approach and the corresponding comparison with the known results of solving the problem considered in this work obtained within the framework of the normal model are absent. In addition, insufficient attention is paid to the search for methods of obtaining consistent solutions. This work to some extent fills these gaps. This work uses non-parametric statistical methods and theory of simultaneous hypothesis testing to address these problems. This paper proposes a procedure for comparative analysis of the efficiency of several units within a network organization with a small volume of observations based on the Mann–Whitney tests. We carry out a comparison of the results obtained from the proposed non-parametric procedure with results based on extensions of Student’s t-tests. We propose a method for reducing the number of compatibility problems based on the search for an appropriate significance level. We provide an example of a fully consistent comparison of the efficiency of branch operations.
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Wang, Hao, Long Zheng y Shunhuai Chen. "Marine Propeller Optimization Based on a Novel Parametric Model". Mathematical Problems in Engineering 2022 (30 de marzo de 2022): 1–19. http://dx.doi.org/10.1155/2022/5612793.
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This paper presents a novel parametric model of marine propellers based on Non-Uniform Rational B-Splines. It involves eight parameters and five categories of spanwise parameter distributions, which are utilized for determining hydrofoil and blade shapes. 20 different hydrofoils and 5 types of well-known marine propellers are employed to detect the accuracy of the proposed parametric model. Furthermore, a propeller optimization problem was addressed with the aid of the parametric model. In the propeller optimization problem, a common AU-series propeller is treated as the baseline propeller. The proposed parametric model is used for the representation and deformation of the propeller geometric model. A hydrodynamic performance evaluation model is developed based on gene expression programming. Also, non-dominated sorting genetic algorithm II is used in the applications of the propeller optimization problem. The results demonstrate that the accuracy of the proposed parametric model satisfies the engineering requirements well, and a propeller with higher efficiency than the baseline propeller can be derived by settling the propeller optimization problem.
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Shaheed, M. H. y M. O. Tokhi. "Dynamic modelling of a single-link flexible manipulator: parametric and non-parametric approaches". Robotica 20, n.º 1 (enero de 2002): 93–109. http://dx.doi.org/10.1017/s0263574701003678.
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This paper presents an investigation into the development of parametric and non-parametric approaches for dynamic modelling of a flexible manipulator system. The least mean squares, recursive least squares and genetic algorithms are used to obtain linear parametric models of the system. Moreover, non-parametric models of the system are developed using a non-linear AutoRegressive process with eXogeneous input model structure with multi-layered perceptron and radial basis function neural networks. The system is in each case modelled from the input torque to hub-angle, hub-velocity and end-point acceleration outputs. The models are validated using several validation tests. Finally, a comparative assessment of the approaches used is presented and discussed in terms of accuracy, efficiency and estimation of the vibration modes of the system.
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lo Storto, Corrado. "A Non Parametric Approach for Measuring the Operational Efficiency of Water Service Providers". Applied Mechanics and Materials 409-410 (septiembre de 2013): 108–13. http://dx.doi.org/10.4028/www.scientific.net/amm.409-410.108.
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This paper presents a benchmarking study that measures operational efficiency of water service providers. The problem of measuring the operational efficiency of water suppliers is addressed by adopting a non parametric approach based on Data Envelopment Analysis. The benchmarking model uses both physical infrastructure network and financial variables. The model is implemented calculating efficiencies of 53 Italian service providers. Results show that there are important operational inefficiencies, mostly due to scale diseconomies.
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S. Barr, Richard, Lawrence M. Seiford y Thomas F. Siems. "Forecasting Bank Failure: A Non-Parametric Frontier Estimation Approach". Recherches économiques de Louvain 60, n.º 4 (diciembre de 1994): 417–29. http://dx.doi.org/10.1017/s0770451800004590.
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SummaryThe dramatic rise in bank failures over the last decade has led to a search for leading indicators so that costly bailouts might be avoided. While the quality of a bank’s management is generally acknowledged to be a key contributor to institutional collapse, it is usually excluded from early-warning models for lack of a metric. This paper describes a new approach for quantifying a bank’s managerial efficiency, using a data-envelopment-analysis model that combines multiple inputs and outputs to compute a scalar measure of efficiency. This new metric captures an elusive, yet crucial, element of institutional success: management quality. New failure-prediction models for detecting a bank’s troubled status which incorporate this explanatory variable have proven to be robust and accurate, as verified by in-depth empirical evaluations, cost sensitivity analyses, and comparisons with other published approaches.
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Banik, Anirban, Sushant Kumar Biswal, Mrinmoy Majumder y Tarun Kanti Bandyopadhyay. "Development of an adaptive non-parametric model for estimating maximum efficiency of disc membrane". International Journal of Convergence Computing 3, n.º 1 (2018): 3. http://dx.doi.org/10.1504/ijconvc.2018.091111.
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Banik, Anirban, Sushant Kumar Biswal, Tarun Kanti Bandyopadhyay y Mrinmoy Majumder. "Development of an adaptive non-parametric model for estimating maximum efficiency of disc membrane". International Journal of Convergence Computing 3, n.º 1 (2018): 3. http://dx.doi.org/10.1504/ijconvc.2018.10012224.
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Bagdadioglu, Necmiddin, Catherine M. Waddams Price y Thomas G. Weyman-Jones. "Efficiency and ownership in electricity distribution: A non-parametric model of the Turkish experience". Energy Economics 18, n.º 1-2 (abril de 1996): 1–23. http://dx.doi.org/10.1016/0140-9883(95)00042-9.
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Alahiane, Mohamed, Idir Ouassou, Mustapha Rachdi y Philippe Vieu. "High-Dimensional Statistics: Non-Parametric Generalized Functional Partially Linear Single-Index Model". Mathematics 10, n.º 15 (30 de julio de 2022): 2704. http://dx.doi.org/10.3390/math10152704.
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We study the non-parametric estimation of partially linear generalized single-index functional models, where the systematic component of the model has a flexible functional semi-parametric form with a general link function. We suggest an efficient and practical approach to estimate (I) the single-index link function, (II) the single-index coefficients as well as (III) the non-parametric functional component of the model. The estimation procedure is developed by applying quasi-likelihood, polynomial splines and kernel smoothings. We then derive the asymptotic properties, with rates, of the estimators of each component of the model. Their asymptotic normality is also established. By making use of the splines approximation and the Fisher scoring algorithm, we show that our approach has numerical advantages in terms of the practical efficiency and the computational stability. A computational study on data is provided to illustrate the good practical behavior of our methodology.
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Miljatović, Aleksandar, Veljko Vukoje y Dragana Tekić. "Applying a non-parametric efficiency analysis to evaluate farm economic viability". Journal on Processing and Energy in Agriculture 26, n.º 1 (2022): 11–14. http://dx.doi.org/10.5937/jpea26-36642.
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The aim of this research is to investigate technical efficiency in different types of farming in Republic of Serbia and then to determine achieved level of farm economic viability. The research is based on FADN data from 2020 year. An input-oriented data envelopment analysis method with variable return to scale is used for calculating farm technical efficiency. One output and four input variables are used in the model. Research has shown that farm technical efficiency in Serbia is on relatively low level (0.346). This indicates that there are significant reserves for potentially input reduction, without output reducing. According to types of farming the most efficient farms are the ones involved in horticulture production (0.542), followed by granivores (0.458) and vineyards and fruits (0.433), while the least efficient are dairy production (0.292). It is noticeable that more intensive types of farming have better output-input ratio, which indicates that those farms reached higher economic viability level. Of course, farm economic viability is wider term and further research should be directed at one comprehensive farm economic viability analysis which would take into consideration other relevant productivity indicators as well as profitability, liquidity and stability indicators. Thereby, considering FADN base limitations that are particularly noticeable when calculate liquidity and stability indicators, is necessary to continuously work on data quality improvement and to make the whole system better.
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Miljatović, Aleksandar, Veljko Vukoje y Dragana Tekić. "Applying a non-parametric efficiency analysis to evaluate farm economic viability". Journal on Processing and Energy in Agriculture 26, n.º 1 (2022): 11–14. http://dx.doi.org/10.5937/jpea26-36642.
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The aim of this research is to investigate technical efficiency in different types of farming in Republic of Serbia and then to determine achieved level of farm economic viability. The research is based on FADN data from 2020 year. An input-oriented data envelopment analysis method with variable return to scale is used for calculating farm technical efficiency. One output and four input variables are used in the model. Research has shown that farm technical efficiency in Serbia is on relatively low level (0.346). This indicates that there are significant reserves for potentially input reduction, without output reducing. According to types of farming the most efficient farms are the ones involved in horticulture production (0.542), followed by granivores (0.458) and vineyards and fruits (0.433), while the least efficient are dairy production (0.292). It is noticeable that more intensive types of farming have better output-input ratio, which indicates that those farms reached higher economic viability level. Of course, farm economic viability is wider term and further research should be directed at one comprehensive farm economic viability analysis which would take into consideration other relevant productivity indicators as well as profitability, liquidity and stability indicators. Thereby, considering FADN base limitations that are particularly noticeable when calculate liquidity and stability indicators, is necessary to continuously work on data quality improvement and to make the whole system better.
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Ikapel, Francis O., Gregory S. Namusonge y Maurice M. Sakwa. "Determinants of Banking Sector Efficiency in Kenya: Application of Non-parametric Data Envelopment Analysis (DEA) Model". Asian Journal of Economics, Business and Accounting 23, n.º 13 (12 de mayo de 2023): 18–28. http://dx.doi.org/10.9734/ajeba/2023/v23i13991.
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The financial system plays an important role in the economic development and financial stability of a country. Banks play a critical role in facilitating stability of the financial system and economic development. Evaluating the determinants of banking efficiency therefore provides insight to establish the target factors that influence efficiency to facilitate inefficiency identification and elimination.
The study’s objective was to evaluate the determinants of banking sector efficiency in Kenya for the period 2006 to 2017. Secondary data were collected from the annual reports and financial statements of 10 commercial banks listed on the Nairobi Securities Exchange (NSE). The analysis was carried out in two stages. In the first stage, the non-parametric Data Envelopment Analysis (DEA) approach was used to compute the efficiency scores. In the second stage, panel regression analysis was then performed to evaluate the determinants of efficiency. The results showed that Capital Adequacy and Market Capitalization are significant in determining the Efficiency of a bank, p =0.0315< 0.05 and p=0.0253< 0.05 respectively. Further, bank size (p = 0.000< 0.05), capital adequacy (p = 0.0014< 0.05), leverage (p = 0.0000< 0.05) and Liquidity risk (p = 0.0000< 0.05) have a significant effect on Scale Efficiency. Market capitalization (p = 0.5056>0.05) is statistically insignificant in influencing the Scale Efficiency of the bank. From the findings, the study, therefore, concludes that, bank size, capital adequacy, liquidity risk, leverage and market capitalization have a significant effect on bank efficiency. The study recommends that bank managers should focus on improving management quality by ensuring compliance with prudential guidelines issued by the Central Bank of Kenya. Particularly, bank managers should ensure capital adequacy and market capitalization requirements are met since they are found to be the key drivers of efficiency and performance. Further, maintaining an optimal bank size, market capitalization, appropriate liquidity risk and leverage level is significant in guaranteeing improved performance.
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Nemes, Szilárd, Andreas Gustavsson y Alexandra Jauhiainen. "Focused Information Criterion for Restricted Mean Survival Times: Non-Parametric or Parametric Estimators". Entropy 24, n.º 5 (16 de mayo de 2022): 713. http://dx.doi.org/10.3390/e24050713.
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Restricted Mean Survival Time (RMST), the average time without an event of interest until a specific time point, is a model-free, easy to interpret statistic. The heavy reliance on non-parametric or semi-parametric methods in the survival analysis has drawn criticism, due to the loss of efficacy compared to parametric methods. This assumes that the parametric family used is the true one, otherwise the gain in efficacy might be lost to interpretability problems due to bias. The Focused Information Criterion (FIC) considers the trade-off between bias and variance and offers an objective framework for the selection of the optimal non-parametric or parametric estimator for scalar statistics. Herein, we present the FIC framework for the selection of the RMST estimator with the best bias-variance trade-off. The aim is not to identify the true underling distribution that generated the data, but to identify families of distributions that best approximate this process. Through simulation studies and theoretical reasoning, we highlight the effect of censoring on the performance of FIC. Applicability is illustrated with a real life example. Censoring has a non-linear effect on FICs performance that can be traced back to the asymptotic relative efficiency of the estimators. FICs performance is sample size dependent; however, with censoring percentages common in practical applications FIC selects the true model at a nominal probability (0.843) even with small or moderate sample sizes.
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Lita, Iulian y Tănase Stamule. "Using non-parametric technical data envelopment analysis - DEA, for measuring productive technical efficiency". Proceedings of the International Conference on Business Excellence 12, n.º 1 (1 de mayo de 2018): 533–43. http://dx.doi.org/10.2478/picbe-2018-0048.
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Abstract The following study is, in addition to a reassessment of literature and an analysis based on non-parametrical techniques based on linear programming. The analysis based on the Data Envelopment Analisys (DEA) technique will be used to see whether the model that we have used has a significant importance, if there are any substantial differences between the efficiency scores obtained or estimated through various methods. The theoretical part, based on the DEA technique will be analysed under the influence of both the works of Farell(1957), and also Charnes, Cooper, Rhodes(1978), Banker, Charnes, Cooper(1984) and other newer models. The dissolution of efficiency scores obtained through the CRS-DEA model has been studied for a long time into two different components: One is linked with the scale inefficiency and the other one represents the pure technical inefficiency. This dissolution can be done by using the CRS model with technology when not all the companies are operating at the optimum level, i.e. through the simultaneous application on the same set of data of the CRS and VRS models. In this study, the main non-parametrical Data Envelopment Analysis method is presented (Wu, Fan, Zhou, Zhou, 2012; Halkos, Tzeremes, 2009) and its application on a group of 42 companies (The headquarters of a top commercial bank in Romania - S.C. BRD GROUPE SOCIÉTÉ GÉNÉRALE ), based on the information gained in the years 2016-2017. This paper is original because it combines the already developed method with new techniques, in order to link together economic factors and operational research and leaves more room for future researches with the purpose of further assessing and changing the performance of every decisional unit under the influence of the environmental factors.
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Shabani, Amir, Gholam Reza Faramarzi, Reza Farzipoor Saen y Mohsen Khodakarami. "Simultaneous evaluation of efficiency, input effectiveness, and output effectiveness". Benchmarking: An International Journal 24, n.º 7 (2 de octubre de 2017): 1854–70. http://dx.doi.org/10.1108/bij-10-2015-0096.
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Purpose The purpose of this paper is to develop a data envelopment analysis (DEA) technique that simultaneously measures efficiency and effectiveness to provide a comprehensive appraisal of the productivity. Additionally, an algorithm is recommended to determine targets that are used for measuring effectiveness. Design/methodology/approach In this paper, for measuring productivity, a new methodology based on non-parametric mathematical DEA technique was presented. The proposed procedure is able to compute the efficiency input effectiveness, and output effectiveness, simultaneously. Findings By comparing with previous models, the authors’ proposed integrated model generates more detailed results and has more discriminating power. Originality/value To the best of the authors knowledge, there is not any study in which a non-parametric mathematical approach measures productivity through simultaneous combining of the effectiveness, including input effectiveness, and output effectiveness, and the efficiency.
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Mirmozaffari, Mirpouya, Reza Yazdani, Elham Shadkam, Seyed Mohammad Khalili, Leyla Sadat Tavassoli y Azam Boskabadi. "A Novel Hybrid Parametric and Non-Parametric Optimisation Model for Average Technical Efficiency Assessment in Public Hospitals during and Post-COVID-19 Pandemic". Bioengineering 9, n.º 1 (27 de diciembre de 2021): 7. http://dx.doi.org/10.3390/bioengineering9010007.
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The COVID-19 pandemic has had a significant impact on hospitals and healthcare systems around the world. The cost of business disruption combined with lingering COVID-19 costs has placed many public hospitals on a course to insolvency. To quickly return to financial stability, hospitals should implement efficiency measure. An average technical efficiency (ATE) model made up of data envelopment analysis (DEA) and stochastic frontier analysis (SFA) for assessing efficiency in public hospitals during and after the COVID-19 pandemic is offered. The DEA method is a non-parametric method that requires no information other than the input and output quantities. SFA is a parametric method that considers stochastic noise in data and allows statistical testing of hypotheses about production structure and degree of inefficiency. The rationale for using these two competing approaches is to balance each method’s strengths, weaknesses and introduce a novel integrated approach. To show the applicability and efficacy of the proposed hybrid VRS-CRS-SFA (VCS) model, a case study is presented.
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Voskoboynikov, Yuri y Vasilisa Boeva. "Non-parametric identification algorithms for complex engineering systems". Science Bulletin of the Novosibirsk State Technical University, n.º 4 (18 de diciembre de 2020): 47–64. http://dx.doi.org/10.17212/1814-1196-2020-4-47-64.
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In a practice, it often happens that complex engineering systems consist of several interconnected different-type simpler subsystems. An adequate model formulation for every subsystem is impractical due to the complexity of physical processes proceeding in the subsystem. In such cases, a non-detailed black-box model is commonly used. For stationary linear systems (or subsystems), the connection between an input and an output of the black-box is defined by the Volterra integral equation of the first kind with an undetermined difference kernel also known as an impulse response in the automatic control theory. It is necessary to evaluate the unknown impulse response to use the black-box model .This statement is a non-parametric identification problem. For complex systems, the problem needs to be solved both for a whole system and for every isolated subsystem that makes identification substantially complex. Formally, impulse response evaluation is a solution of the integral equation of the first kind for its kernel over registered noise-contaminated discrete input and output values. This problem is ill-posed because of possible solution instability regarding measurement noises in initial data. To find a unique stable solution regularizing algorithms are used, but specific input and output signals in impulse response identification experiments do not allow applying computational methods of these algorithms (system of linear equations or discrete Fourier transformation). In this paper, the authors propose two specific-considering identification algorithms for complex engineering systems. In these algorithms, smoothing cubic splines are used for stable calculation of first derivatives of identified system signals. The results of the complex “Heater-Blower-Room” system identification prove the efficiency of algorithms proposed.
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Guk, Aleksander P. y Larisa G. Evstratova. "Research of efficiency of the statistical non-parametric pattern recognition models for forest land classification". E3S Web of Conferences 75 (2019): 01002. http://dx.doi.org/10.1051/e3sconf/20197501002.
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The principles of the creation of pattern recognition models, based on using multispectral imagery of forest land, have been analyzed. The statistical non-parametric model has been suggested as a basic pattern recognition model and the probability density function - as a recognition feature. Efficiency of the different quality criteria has been discussed. The main directions for improving the pattern recognition models are regarded.
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Zhang, Rui, Christian Walder y Marian-Andrei Rizoiu. "Variational Inference for Sparse Gaussian Process Modulated Hawkes Process". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 04 (3 de abril de 2020): 6803–10. http://dx.doi.org/10.1609/aaai.v34i04.6160.
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The Hawkes process (HP) has been widely applied to modeling self-exciting events including neuron spikes, earthquakes and tweets. To avoid designing parametric triggering kernel and to be able to quantify the prediction confidence, the non-parametric Bayesian HP has been proposed. However, the inference of such models suffers from unscalability or slow convergence. In this paper, we aim to solve both problems. Specifically, first, we propose a new non-parametric Bayesian HP in which the triggering kernel is modeled as a squared sparse Gaussian process. Then, we propose a novel variational inference schema for model optimization. We employ the branching structure of the HP so that maximization of evidence lower bound (ELBO) is tractable by the expectation-maximization algorithm. We propose a tighter ELBO which improves the fitting performance. Further, we accelerate the novel variational inference schema to linear time complexity by leveraging the stationarity of the triggering kernel. Different from prior acceleration methods, ours enjoys higher efficiency. Finally, we exploit synthetic data and two large social media datasets to evaluate our method. We show that our approach outperforms state-of-the-art non-parametric frequentist and Bayesian methods. We validate the efficiency of our accelerated variational inference schema and practical utility of our tighter ELBO for model selection. We observe that the tighter ELBO exceeds the common one in model selection.
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MOLLAH, A. SABUR. "TESTING WEAK-FORM MARKET EFFICIENCY IN EMERGING MARKET: EVIDENCE FROM BOTSWANA STOCK EXCHANGE". International Journal of Theoretical and Applied Finance 10, n.º 06 (septiembre de 2007): 1077–94. http://dx.doi.org/10.1142/s021902490700455x.
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Market efficiency is an area of enormous interest in financial literature. Numerous researchers conducted empirical studies in testing weak-form market efficiency in several stock markets and employed various techniques but the empirical evidence is controversial. Triangulation econometric approach is employed to assess the predictability of daily return series of Botswana Stock Exchange (BSE) and to test the null hypothesis of random walk model. The empirical results reject the null hypothesis of random walk model for the daily return series of BSE for the period of 1989–2005 and evidenced serial autocorrelation of return series, which clearly indicate predictability and volatility of security prices of Botswana market. However, the empirical evidence of both non-parametric (Kolmogrov–Smirnov: normality test and run test) and parametric test (Auto-correlation test, Auto-regressive model, ARIMA model) reject the hypothesis of random walk model and indeed violate the notion of weak-form market efficiency.
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Bampatsou, Christina y George Halkos. "Non-Parametric Computational Measures for the Analysis of Resource Productivity". Energies 14, n.º 11 (26 de mayo de 2021): 3114. http://dx.doi.org/10.3390/en14113114.
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In this study, we assumed that 28 European countries (Decision Making Units (DMUs)) aimed to accomplish higher economic outputs, using fewer resources and producing fewer emissions in the form of environmental degradation. In this context, we studied the drivers of total factor productivity change (TFPCH) in DMUs, associated with either managerial capabilities (efficiency change (EC)) or innovations (technical change (TC)) in resource-saving production methods, before and after the integration of CO2 (carbon dioxide) emissions as an additional variable (undesirable output) in the initial model of one output (gross domestic product (GDP)) and five inputs (labor, capital, energy, domestic material consumption and recycled municipal waste). The primary focus of this study is to identify best practices that policymakers can adopt as they attempt to reduce productivity loss. Our results highlight the weak areas of individual countries and seem to indicate the action that should be taken to improve their productivity by taking into consideration the main driving force behind productivity and technical efficiency change. Our findings reveal that an effective use of technological developments is determined as important strategic information for ensuring managerial performance.
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Zhuang, Yan, Ying Guan, Libin Qiu, Meisheng Lai, Ming T. Tan y Pingyan Chen. "A novel rank-based non-parametric method for longitudinal ordinal data". Statistical Methods in Medical Research 27, n.º 9 (8 de enero de 2017): 2775–94. http://dx.doi.org/10.1177/0962280216686628.
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Longitudinal ordinal data are common in biomedical research. Although various methods for the analysis of such data have been proposed in the past few decades, they are limited in several ways. For instance, the constraints on parameters in the proportional odds model may result in convergence problems; the rank-based aligned rank transform method imposes constraints on other parameters and the distributional assumptions with parametric model. We propose a novel rank-based non-parametric method that models the profile rather than the distribution of the data to make an effective statistical inference without the constraint conditions. We construct the test statistic of the interaction first, and then construct the test statistics of the main effects separately with or without the interaction, while “adjusted coefficient” for the case of ties is derived. A simulation study is conducted for comparison between rank-based non-parametric and rank-transformed analysis of variance. The results show that type I errors of the two methods are both maintained closer to the priori level, but the statistical power of rank-based non-parametric is greater than that of rank-transformed analysis of variance, suggesting higher efficiency of the former. We then apply rank-based non-parametric to two real studies on acne and osteoporosis, and the results also illustrate the effectiveness of rank-based non-parametric, particularly when the distribution is skewed.
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Bakr, M. E., M. Nagy y Abdulhakim A. Al-Babtain. "Non-parametric hypothesis testing to model some cancers based on goodness of fit". AIMS Mathematics 7, n.º 8 (2022): 13733–45. http://dx.doi.org/10.3934/math.2022756.
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<abstract> <p>By observing the failure behavior of the recorded survival data, we aim to compare the different processing approaches or the effectiveness of the devices or systems applied in this non-parametric statistical test. We'll apply the proposed strategy of used better than aged in Laplace (UBAL) transform order, which assumes that the data used in the test will either behave as UBAL Property or exponential behavior. If the survival data is UBAL, it means that the suggested treatment strategy is effective, whereas if the data is exponential, the recommended treatment strategy has no negative or positive effect on patients, as indicated in the application section. To guarantee the test's validity, we calculated the suggested test's power in both censored and uncensored data, as well as its efficiency, compared the results to other tests, and then applied the test to a variety of real data.</p> </abstract>
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Shao, Luning, Jianxin You, Tao Xu y Yilei Shao. "Non-Parametric Model for Evaluating the Performance of Chinese Commercial Banks’ Product Innovation". Sustainability 12, n.º 4 (18 de febrero de 2020): 1523. http://dx.doi.org/10.3390/su12041523.
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A thorough analysis of commercial banks’ product innovation performance is essential to promoting bank product innovation capabilities and sustainable development. In this paper, the product innovation performance of commercial banks is defined as the conversion efficiency of input and output factors. The credit risk of product innovation of banks is considered as an undesirable output and incorporated in the performance evaluation system. Depending on whether there is a synchronous relationship between innovation income and risks, a Fixed Correlation model (FCM) and a Variable Correlation model (VCM) are then constructed based on Data Envelopment Analysis (DEA) method for the evaluation of commercial bank product innovation performance. In addition, an output optimization model of the objective function is also constructed to estimate the target income of commercial banks’ product innovation in the FCM and VCM. Finally, the proposed model is applied to Chinese listed commercial banks for estimating the performance and target income of product innovation.
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Hashemian, A. H., M. Garshasbi, M. A. Pourhoseingholi y S. Eskandari. "A Comparative Study of Cox Regression vs. Log-Logistic Regression (with and without its frailty) in Estimating Survival Time of Patients with Colorectal Cancer". Journal of Medical and Biomedical Sciences 6, n.º 1 (13 de junio de 2017): 35–43. http://dx.doi.org/10.4314/jmbs.v6i1.5.
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Colorectal cancer is common and lethal disease with different incidence rate in different parts of the world which is taken into account as the third cause of cancer-related deaths. In the present study, using non-parametric Cox model and parametric Log-logistic model, factors influencing survival of patients with colorectal cancer were evaluated and the models efficiency were compared to provide the best model. This study is conducted on medical records of 1,127 patients with colorectal cancer referred to Taleghani Medical and Training Center of Tehran between 2001 - 2007 and were definitely diagnosed with cancer, pathologically. Semi-parametric Cox model and parametric log-logistic model were fitted. Akaike’s criterion of Cox Snell graph was used to compare the models. To take into account non-measured individual characteristics, frailty was added to Cox and log-logistic models. All calculations were carried out using STATA software version 12 and SPSS version 20.0, at the 0.05 level of significance. From a total of 1,127 patients studied in this research, there were 690 men and 437 women. According to non-parametric Kaplan-Meier method, chances of surviving for 1, 3, 5 and 7 years were 91.16, 73.20, 61.00, and 54.94, respectively. Addition of frailty parameter did not change the model outcome. The results of fitting classified Cox and log-logistic models showed that body mass index (BMI), tumor grade, tumor size, and spread to lymph nodes, were the factors affecting survival time. Based on comparisons, and according to Cox Snell residuals, Cox and log-logistic models had almost identical results; however, because of the benefits of parametric models, in surveying survival time of patients with colorectal cancer, log-logistic can be replaced, as a parametric model, with Cox model.Journal of Medical and Biomedical Sciences (2017) 6(1), 35-43Keywords: Colorectal cancer, Cox regression, Log-logistic model, Cox Snell residual
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Wang, Mingyang, Zhenshan Bing, Xiangtong Yao, Shuai Wang, Huang Kai, Hang Su, Chenguang Yang y Alois Knoll. "Meta-Reinforcement Learning Based on Self-Supervised Task Representation Learning". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 8 (26 de junio de 2023): 10157–65. http://dx.doi.org/10.1609/aaai.v37i8.26210.
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Meta-reinforcement learning enables artificial agents to learn from related training tasks and adapt to new tasks efficiently with minimal interaction data. However, most existing research is still limited to narrow task distributions that are parametric and stationary, and does not consider out-of-distribution tasks during the evaluation, thus, restricting its application. In this paper, we propose MoSS, a context-based Meta-reinforcement learning algorithm based on Self-Supervised task representation learning to address this challenge. We extend meta-RL to broad non-parametric task distributions which have never been explored before, and also achieve state-of-the-art results in non-stationary and out-of-distribution tasks. Specifically, MoSS consists of a task inference module and a policy module. We utilize the Gaussian mixture model for task representation to imitate the parametric and non-parametric task variations. Additionally, our online adaptation strategy enables the agent to react at the first sight of a task change, thus being applicable in non-stationary tasks. MoSS also exhibits strong generalization robustness in out-of-distributions tasks which benefits from the reliable and robust task representation. The policy is built on top of an off-policy RL algorithm and the entire network is trained completely off-policy to ensure high sample efficiency. On MuJoCo and Meta-World benchmarks, MoSS outperforms prior works in terms of asymptotic performance, sample efficiency (3-50x faster), adaptation efficiency, and generalization robustness on broad and diverse task distributions.
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Titko, Jelena, Jelena Stankevičienė y Nataļja Lāce. "MEASURING BANK EFFICIENCY: DEA APPLICATION". Technological and Economic Development of Economy 20, n.º 4 (16 de diciembre de 2014): 739–57. http://dx.doi.org/10.3846/20294913.2014.984255.
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The paper aims to improve the methodology of measuring efficiency of Latvian banks. Efficiency scores were calculated with application of non-parametric frontier technique Data Envelopment Analysis (DEA). Input-oriented DEA model under Variable Returns to Scale (VRS) assumption was used. Potential model variables were selected based on the intermediation and profitability approach. Fourteen alternative models with different inputs-outputs combinations were developed for the research purposes. To substantiate the variables selection for DEA model the received data was processed, using such methods, as correlation analysis, linear regression analysis, analysis of mean values, and two-samples Kolmogorov-Smirnov test. The research results assisted the authors in providing general recommendations about the variables selection for DEA application in the Latvian banking sector. The present research contributes to the existing analytical data on bank performance in Latvia. The empirical findings provide a background for further studies, in particular, the efficiency of Latvian banks could be analysed in the extended time period.
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Shakhashiro, Ahmad, Fakarudin Kamarudin y Ida Md. Yasin. "BANK TECHNICAL EFFICIENCY, PURE TECHNICAL EFFICIENCY AND SCALE EFFICIENCY, DOES ECONOMIC FREEDOM MATTER? EVIDENCE FROM CENTRAL EUROPE". Advanced International Journal of Banking, Accounting and Finance 3, n.º 8 (15 de septiembre de 2021): 76–103. http://dx.doi.org/10.35631/aijbaf.38007.
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The current study attempts to investigate the impact of the limitation of economic freedom on conventional bank technical efficiency and its components (pure technical efficiency and scale efficiency) by using data from the region of central Europe. Non-parametric Data Envelopment Analysis (DEA) is employed to measure the bank's technical efficiency and its components levels. The applied method of estimation consists of “pooled Ordinary Least Square (OLS), Fixed Effect Model (FEM), Random Effect Model (REM), and the Generalized Method of Moments (GMM)” to investigate the influence of economic freedom and other potential determinants on bank efficiency. This study has found that the indicators of Government Spending, Fiscal Health, Business Freedom, Labor Freedom, and Financial Freedom have positive relationships with bank’s technical efficiency, pure technical efficiency, and scale efficiency. Contrariwise, Overall Economic Freedom, Monetary Freedom, and Investment Freedom exhibit a negative impact on a bank’s technical efficiency and its components. Implications from the study permit the related parties to identify the significant dimensions of economic freedom to the efficiency of the banks to ensure better bank performance.
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Du, Xin, Yulong Pei, Wouter Duivesteijn y Mykola Pechenizkiy. "Exceptional spatio-temporal behavior mining through Bayesian non-parametric modeling". Data Mining and Knowledge Discovery 34, n.º 5 (29 de enero de 2020): 1267–90. http://dx.doi.org/10.1007/s10618-020-00674-z.
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Abstract Collective social media provides a vast amount of geo-tagged social posts, which contain various records on spatio-temporal behavior. Modeling spatio-temporal behavior on collective social media is an important task for applications like tourism recommendation, location prediction and urban planning. Properly accomplishing this task requires a model that allows for diverse behavioral patterns on each of the three aspects: spatial location, time, and text. In this paper, we address the following question: how to find representative subgroups of social posts, for which the spatio-temporal behavioral patterns are substantially different from the behavioral patterns in the whole dataset? Selection and evaluation are the two challenging problems for finding the exceptional subgroups. To address these problems, we propose BNPM: a Bayesian non-parametric model, to model spatio-temporal behavior and infer the exceptionality of social posts in subgroups. By training BNPM on a large amount of randomly sampled subgroups, we can get the global distribution of behavioral patterns. For each given subgroup of social posts, its posterior distribution can be inferred by BNPM. By comparing the posterior distribution with the global distribution, we can quantify the exceptionality of each given subgroup. The exceptionality scores are used to guide the search process within the exceptional model mining framework to automatically discover the exceptional subgroups. Various experiments are conducted to evaluate the effectiveness and efficiency of our method. On four real-world datasets our method discovers subgroups coinciding with events, subgroups distinguishing professionals from tourists, and subgroups whose consistent exceptionality can only be truly appreciated by combining exceptional spatio-temporal and exceptional textual behavior.
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Klumpp, Matthias y Dominic Loske. "Order Picking and E-Commerce: Introducing Non-Parametric Efficiency Measurement for Sustainable Retail Logistics". Journal of Theoretical and Applied Electronic Commerce Research 16, n.º 4 (16 de febrero de 2021): 846–58. http://dx.doi.org/10.3390/jtaer16040048.
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Order picking is a crucial but labor- and cost-intensive activity in the retail logistics and e-commerce domain. Comprehensive changes are implemented in this field due to new technologies like AI and automation. Nevertheless, human worker’s activities will be required for quite some time in the future. This fosters the necessity of evaluating manual picker-to-part operations. We apply the non-parametric Data Envelopment Analysis (DEA) to evaluate the efficiency of n = 23 order pickers processing 6109 batches with 865,410 stock keeping units (SKUs). We use distance per location, picks per location, as well as volume per SKU as inputs and picks per hour as output. As the convexity axiom of standard DEA models cannot be fully satisfied when using ratio measures with different denominators, we apply the Free Disposal Hull (FDH) approach that does not assume convexity. Validating the efficiency scores with the company’s efficiency assessment, operationalized by premium payments shows a 93% goodness=of-fit for the proposed model. The formulated non-parametric approach and its empirical application are promising ways forward in implementing empirical efficiency measurements for order picking operations within e-commerce operations.
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Boeva, Vasilisa, Yuri Voskoboinikov y Rustam Mansurov. "Non-parametric identification of thermal control system elements". Analysis and data processing systems, n.º 1 (26 de marzo de 2021): 7–20. http://dx.doi.org/10.17212/2782-2001-2021-1-7-20.
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The thermal control system “Heater-Fan-Room” is represented by three different-type interconnected simpler subsystems. In this paper, a “black-box” whose structure is not specified is used as a mathematical model of the system and subsystems due to complexity of physical processes proceeding in these subsystems. For stationary linear systems, the connection between an input and an output of the “black-box” is defined by the Volterra integral equation of the first kind with an undetermined difference kernel also known as impulse response in the automatic control theory. In such a case, it is necessary to evaluate an unknown impulse response to use the “black-box” model and formulate all subsystems and the system as a whole. This condition complicates significantly the solution search of non-parametric identification problems in the system because an output of one subsystem is an input of another subsystem, so active identification schemes are unappropriated. Formally, an impulse response evaluation is a solution of the integral equation of the first kind for its kernel by registered noise-contaminated discrete input and output values. This problem is ill-posed because of the possible solution instability (impulse response evaluation in this case) relative to measurement noises in initial data. To find a unique stable solution regularizing algorithms are used, but the specificity of the impulse response identification experiment in the “Heater-Fan-Room” system do not allow applying computational methods of these algorithms (a system of linear equations or discrete Fourier transformation). In this paper, the authors propose two specific identification algorithms for complex technical systems. In these algorithms, impulse responses are evaluated using first derivatives of identified system signals that are stably calculated by smoothing cubic splines with an original smoothing parameter algorithm. The results of the complex “Heater-Fan-Room” system modeling and identification prove the efficiency of the algorithms proposed. Acknowledgments: The reported study was funded by RFBR, project number 20-38-90041.
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Pang, Qiong y Xijian Hu. "INLA Estimation of Semi-Variable Coefficient Spatial Lag Model—Analysis of PM2.5 Influencing Factors in the Context of Urbanization in China". Mathematics 12, n.º 7 (23 de marzo de 2024): 953. http://dx.doi.org/10.3390/math12070953.
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The Semi-variable Coefficient Spatial Lag Model (SVC-SLM) not only addresses the “dimension disaster” associated with the Varying Coefficient Spatial Lag Model(VC-SLM), but also overcomes the non-linear problem of the variable coefficient, and fully explores the hidden information of the model. In this paper, INLA is firstly used to estimate the parameters of (SVC-SLM) by using B-spline to deal with the non-parametric terms, and the comparative experimental results show that the INLA algorithm is much better than MCMCINLA in terms of both time efficiency and estimation accuracy. For the problem of identifying the constant coefficient terms in the SVC-SLM, the bootstrap test is given based on the residuals. Taking the PM2.5 data of 31 provinces in mainland China from 2015 to 2020 as an empirical example, parametric, non-parametric, and semi-parametric perspectives establish three models of Spatial Lag Model (SLM), VC-SLM, SVC-SLM, which explore the relationship between the covariate factors and the level of urbanization as well as their impacts on the concentration of PM2.5 in the context of increasing urbanization; among the three models, the SVC-SLM has the smallest values of DIC and WAIC, indicating that the SVC-SLM is optimal.
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Preeti y Supriyo Roy. "Operational Performance Modelling of Indian Banks: A Data Envelopment Analysis Approach". Paradigm: A Management Research Journal 26, n.º 1 (junio de 2022): 29–49. http://dx.doi.org/10.1177/09718907221103666.
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The rising level of non-performing loans (NPLs) posits risk on the operational working of the banking sector. The study focuses on developing an operational performance model for banks by considering the NPLs. The study uses non-parametric methodology to develop a non-oriented and non-radial Data Envelopment Analysis (DEA) model with NPLs as undesirable output. The dataset of 39 Indian commercial banks for period of 5 years is selected for the study. The findings of the study prove that considering risk into performance modelling leads to an unbiased efficiency indicator. Also, the non-parametric test confirms the relationship between operational efficiency and ownership. The study uses non-orientation modelling results to reveal inefficient sources within under-performing banks. As per the findings, slack variable analysis reveals two problem areas: ‘fixed assets’ and ‘NPLs’. A higher focus on improving utilization of fixed assets as well as controlling the level of rising NPL (risk) is highly significant for benchmarking performance. Overall, the study supports the business decision to control excess inputs and outputs for banks to achieve the efficient frontier. Significant managerial implications are linked to findings of the study focusing towards performance improvement of banks.
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Jovanović, Mihailo, Slobodan Nedeljković, Milan Ranđelović, Gordana Savić, Vladica Stojanović, Vladimir Stojanović y Dragan Ranđelović. "A Multicriteria Decision Aid-Based Model for Measuring the Efficiency of Business-Friendly Cities". Symmetry 12, n.º 6 (17 de junio de 2020): 1025. http://dx.doi.org/10.3390/sym12061025.
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Local self-government has the task of enabling stable economic development, in addition to enabling a normal quality of life for citizens. This is why the state government should provide guidelines that will improve the local business climate, and by doing so enable local economic development. This can be done through the introduction of a business-friendly certification procedure, which is influenced by uncertain inputs and influences many output factors. Each local government has the important task of determining its rank of efficiency in this process. A number of methodologies developed to solve this problem are generally divided into two groups: Parametric and non-parametric. These two groups of methodologies could provide quite different results. Therefore, the purpose of this paper was to create a model using both approaches to achieve a balanced symmetrical approach that produces better results than each approach individually. For this purpose, the paper describes a multicriteria decision aid-based model of optimization to evaluate the effectiveness of this process, integrating classification, data envelopment analysis, and stochastic frontier analysis, as well as its application in a case study of business-friendly certification in the Republic of Serbia.
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Al-Assa'd, Tamer y Johannes Sauer. "The performance of water utilities in Jordan". Water Science and Technology 62, n.º 4 (1 de agosto de 2010): 803–8. http://dx.doi.org/10.2166/wst.2010.907.
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This paper aims to measure the relative performance of Jordan's water utilities for water sector (WS) and wastewater sector (WWS), and to investigate the major factors behind their inefficiencies. DEA (non-parametric method) and Tobit model (parametric method) were used at two stages. At the first stage DEA was used to evaluate the utilities' efficiency and to investigate the utilities' scale effect on efficiency. At the second stage Tobit model (regression) is applied to determine the impact of the non-controllable factors on utilities' inefficiencies where the efficiency score is the dependent variable in the regression. The results of DEA showed that there is a potential to reduce inputs level: water supply and operational expense (OPEX) for WS, and treated wastewater and OPEX for WWS, by around 15–20 and 23–27%, respectively. Aqaba and Jarash utilities are the most efficient utilities in the WS, while it is Amman utility in the WWS. The utility size has relatively moderate effect on the relative performance. It is concluded that the medium utility size for WS and large utility size for WWS is the most appropriate. Tobit model results indicate that commercialization activities have a clear positive impact on efficiency improvement for both sectors.
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Yao Séraphin, PRAO y DIABATE Salimata. "The Determinants of the Efficiency of Ivorian Commercial Banks: A Study Using the Non-Parametric Approach". International Business Research 15, n.º 11 (27 de octubre de 2022): 30. http://dx.doi.org/10.5539/ibr.v15n11p30.
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The objective of this study is to analyze the determinants of banking efficiency in Côte d'Ivoire. To achieve this objective, we used annual data covering the period from 2004 to 2017, for fifteen Ivorian banks. Methodologically, we first used the non-parametric data envelopment analysis (DEA) method to determine the efficiency scores. The results show that Ivorian banks are technically inefficient. Second, we used a Tobit model to identify the determinants of bank efficiency. The Tobit regression identifies return on equity, regulatory capital, size, and credit as the main determinants of the technical efficiency of Ivorian banks. In addition, bank liquidity and ownership, GDP growth rate, and inflation are sources of inefficiency in Ivorian banks. The study recommends that banks manage their resources rationally to finance the economy efficiently. At the level of the monetary authorities, they should ensure that banks apply regulatory standards.
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Tao, Chong, Jon Chow, Lei Sui, Anan Wang, Gerard Bottino, Peter Evans, David Newman, Raj Venuturumilli, Jon Lowe y Johan Liekens. "Validation of a New Method for Continuous Flare Combustion Efficiency Monitoring". Atmosphere 15, n.º 3 (14 de marzo de 2024): 356. http://dx.doi.org/10.3390/atmos15030356.
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A new method is described for calculating flare combustion efficiency (CE) and destruction and removal efficiency (DRE) using a numerical parametric model. The method combines key variables that affect flare performance including the flare vent gas net heating value (NHV), flare design, flow rate, exit velocity, and inert gas composition, alongside the environmental influence of crosswind speed. Each effect is characterized using a parametric model derived from experimental testing data and computational fluid dynamics (CFD). The inclusion of CFD allows the model to be extended into the high-wind conditions that cannot be adequately controlled for in empirical testing yet represent some of the most challenging conditions in which to maintain good combustion. This new parametric model method (PMM) is coupled with ultrasonic flowmeters from which the molecular weight and net heating value of the flare gas can be derived using the vent gas speed of sound measurement. In doing so, this method provides a reliable continuous flare combustion efficiency measure that can be deployed at scale with minimum hardware updates. The system was verified using an extractive sampling method with tests conducted on three full-scale industrial flares including non-assisted, single-arm pressure-assisted, and multi-arm pressure-assisted flare designs. A total of seventy valid test points were carried out with varying flow rate and flare gas heating value, covering a CE range from 46–100%. The uncertainty of the method was assessed using both traditional error propagation and Monte Carlo methodology. The results from the new method agree with the extractive method to within 0.8% in the ≥98% DRE region where flares are expected to operate to limit the impacts of flaring as a source of methane as a greenhouse gas. Uncertainty analysis revealed that the larger DRE discrepancy for DRE ≤ 98% correlates to the measurement uncertainties for both methods.
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Ospina, Raydonal, Samuel G. F. Baltazar, Víctor Leiva, Jorge Figueroa-Zúñiga y Cecilia Castro. "Robust Semi-Parametric Inference for Two-Stage Production Models: A Beta Regression Approach". Symmetry 15, n.º 7 (4 de julio de 2023): 1362. http://dx.doi.org/10.3390/sym15071362.
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The data envelopment analysis is related to a non-parametric mathematical tool used to assess the relative efficiency of productive units. In different studies on productive efficiency, it is common to employ semi-parametric procedures in two stages to determine whether any exogenous factors of interest affect the performance of productive units. However, some of these procedures, particularly those based on conventional statistical inference, generate inconsistent estimates when dealing with incoherent data-generating processes. This inconsistency arises due to the efficiency scores being limited to the unit interval, and the estimated scores often exhibit serial correlation and have limited observations. To address such inconsistency, several strategies have been suggested, with the most well-known being an algorithm based on a parametric bootstrap procedure using the truncated normal distribution and its regression model. In this work, we present a modification of this algorithm that utilizes the beta distribution and its regression structure. The beta model allows for better accommodation of asymmetry in the data distribution. Our proposed algorithm introduces inferential characteristics that are superior to the original algorithm, resulting in a more statistically coherent data-generating process and improving the consistency property. We have conducted computational experiments that demonstrate the improved results achieved by our proposal.
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Kemiveš, Aleksandar, Lidija Barjaktarović, Milan Ranđelović, Milan Čabarkapa y Dragan Ranđelović. "Assessing the Efficiency of Foreign Investment in a Certification Procedure Using an Ensemble Machine Learning Model". Mathematics 12, n.º 7 (28 de marzo de 2024): 1020. http://dx.doi.org/10.3390/math12071020.
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Many methods exist for solving the problem of evaluating efficiency in different processes. They are divided into two basic groups, parametric and non-parametric methods, which can have significant differences in the results. In this study, the authors consider the process of assessing the business climate depending on realized foreign investments. Due to the expected difference in efficiency assessment using different approaches, the goal of this paper is to create an optimization model of an ensemble for efficiency assessment that uses both types of methods with the aim of creating a symmetrical approach that achieves better results than each type of method individually. The proposed solution simultaneously analyzes the impact of different factors on foreign investments in order to determine the most important factors and thus enable each local government to ensure the best possible efficiency in this process. The innovative idea of this study is in the inclusion of classification and feature selection methods of machine learning to fulfill the set goal. Our research, focused on a specific case study in various cities across the Republic of Serbia, evaluated the effectiveness of that process. This study extends previous research and confirms the published results, highlighting the advantages of the newly proposed model.
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Copeland, Mary Kay y Emilyn Cabanda. "Efficiency Analysis of the U.S. Publicly Held Insurance Industry". International Journal of Information Systems in the Service Sector 10, n.º 1 (enero de 2018): 1–15. http://dx.doi.org/10.4018/ijisss.2018010101.
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This paper aims to measure and analyze the efficiency of the US publicly-held insurance industry from 2011 to 2013. The paper uses a two-stage efficiency model: (1) data envelopment analysis (DEA), a non-parametric model for measuring the efficiency of 141 panel data of US publicly-held insurance firms, and (2) stochastic Tobit regression model for determining associations between insurers' financial performance and efficiency. Three significant findings are obtained: (1) There is no evidence that US insurance firms consistently improve in efficiency over time using the input-output mix. (2) There is an overall positive significant association between insurers' financial performance and technical efficiency at a very high confidence level. (3) Type of insurance is found to have a negative and significant effect on efficiency. These new findings add empirical evidence to the efficiency analysis of the US insurance industry.
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Sonkariya, Anjali y Shiv Prasad Yadav. "Development of intuitionistic fuzzy cost efficiency model in data envelopment analysis". Notes on Intuitionistic Fuzzy Sets 29, n.º 3 (octubre de 2023): 298–317. http://dx.doi.org/10.7546/nifs.2023.29.3.298-317.
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Data envelopment analysis (DEA) is a non-parametric linear programming (LP) based technique to measure the relative efficiencies of decision-making units (DMUs). The conventional DEA models assume that input-output data is crisp, which may not always be feasible in practical situations due to the presence of ambiguity and imprecision. Therefore, to handle uncertain and imprecise data, the concept of intuitionistic fuzzy sets (IFS) has been introduced. In this study, the relative efficiencies of DMUs with uncertain data will be determined. For this reason, the conventional cost efficiency (CE) model of DEA is extended to IF environment. Also, the lower and upper-cost efficiency models are developed using α-cut and β-cut approach. The data for inputs, outputs and input prices are considered intuitionistic fuzzy numbers (IFNs), in particular triangular intuitionistic fuzzy numbers (TIFNs). To demonstrate the practical application of the proposed intuitionistic fuzzy cost efficiency models (IFCEMs), a numerical example is presented.
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Javed, M. Ishaq, Sultan Ali Adil, Sarfaraz Hassan y Asghar Ali. "An Efficiency Analysis of Punjab’s Cotton-Wheat System". LAHORE JOURNAL OF ECONOMICS 14, n.º 2 (1 de julio de 2009): 97–124. http://dx.doi.org/10.35536/lje.2009.v14.i2.a4.
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This study examines the technical, allocative, and economic efficiencies of the cotton-wheat farming system in Punjab, Pakistan. It also investigates the determinants of these efficiencies using a non-parametric data envelopment analysis (DEA) technique. Technical, allocative, and economic inefficiency scores are separately regressed on socioeconomic and farm-specific variables to identify the sources of inefficiency using a Tobit regression model. The mean technical, allocative, and economic efficiencies calculated for the system were 0.87, 0.44, and 0.37, respectively. Our results indicate that years of schooling and the number of contacts with extension agents have a negative impact on the inefficiency of cotton-wheat farming in Punjab.