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Статті в журналах з теми "Generalised regression estimators"
Zhang, Li-Chun. "Generalised Regression Estimation Given Imperfectly Matched Auxiliary Data." Journal of Official Statistics 37, no. 1 (March 1, 2021): 239–55. http://dx.doi.org/10.2478/jos-2021-0010.
Повний текст джерелаWada, Kazumi, Keiichiro Sakashita, and Hiroe Tsubaki. "Robust Estimation for a Generalised Ratio Model." Austrian Journal of Statistics 50, no. 1 (February 3, 2021): 74–87. http://dx.doi.org/10.17713/ajs.v50i1.994.
Повний текст джерелаMohammed, M. A., Huda M. Alshanbari, and Abdal-Aziz H. El-Bagoury. "Application of the LINEX Loss Function with a Fundamental Derivation of Liu Estimator." Computational Intelligence and Neuroscience 2022 (March 14, 2022): 1–9. http://dx.doi.org/10.1155/2022/2307911.
Повний текст джерелаLaroussi, Ilhem. "A generalised censored least squares and smoothing spline estimators of regression function." International Journal of Mathematics in Operational Research 20, no. 4 (2021): 506. http://dx.doi.org/10.1504/ijmor.2021.120102.
Повний текст джерелаSutradhar, B. "Miscellanea. On the efficiency of regression estimators in generalised linear models for longitudinal data." Biometrika 86, no. 2 (June 1, 1999): 459–65. http://dx.doi.org/10.1093/biomet/86.2.459.
Повний текст джерелаKhare, B. B., and Sanjay Kumar. "Generalised chain ratio-in-regression estimators for population mean using two-phase sampling in the presence of non-response." Journal of Information and Optimization Sciences 36, no. 4 (June 9, 2015): 317–38. http://dx.doi.org/10.1080/02522667.2014.926706.
Повний текст джерелаSlaoui, Y., and A. Jmaei. "Recursive and non-recursive regression estimators using Bernstein polynomials." Theory of Stochastic Processes 26(42), no. 1 (December 27, 2022): 60–95. http://dx.doi.org/10.37863/tsp-2899660400-77.
Повний текст джерелаDEVITA, HANY, I. KOMANG GDE SUKARSA, and I. PUTU EKA N. KENCANA. "KINERJA JACKKNIFE RIDGE REGRESSION DALAM MENGATASI MULTIKOLINEARITAS." E-Jurnal Matematika 3, no. 4 (November 28, 2014): 146. http://dx.doi.org/10.24843/mtk.2014.v03.i04.p077.
Повний текст джерелаShaheen, Nazia, Muhammad Nouman Qureshi, Osama Abdulaziz Alamri, and Muhammad Hanif. "Optimized inferences of finite population mean using robust parameters in systematic sampling." PLOS ONE 18, no. 1 (January 23, 2023): e0278619. http://dx.doi.org/10.1371/journal.pone.0278619.
Повний текст джерелаSÖKÜT AÇAR, Tuğba. "Kibria-Lukman Estimator for General Linear Regression Model with AR(2) Errors: A Comparative Study with Monte Carlo Simulation." Journal of New Theory, no. 41 (December 31, 2022): 1–17. http://dx.doi.org/10.53570/jnt.1139885.
Повний текст джерелаДисертації з теми "Generalised regression estimators"
Bae, Deok Hwan. "Models for target detection times." Thesis, Monterey, California. Naval Postgraduate School, 1989. http://hdl.handle.net/10945/27141.
Повний текст джерелаSome battlefield models have a component in them which models the time it takes for an observer to detect a target. Different observers may have different mean detection times due to various factors such as the type of sensor used, environmental conditions, fatigue of the observer, etc. Two parametric models for the distribution of time to target detection are considered which can incorporate these factors. Maximum likelihood estimation procedures for the parameters are described. Results of simulation experiments to study the small sample behavior of the estimators are presented.
http://archive.org/details/modelsfortargetd00baed
Major, Korean Air Force
Santos, Helton Saulo Bezerra dos. "Essays on Birnbaum-Saunders models." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2013. http://hdl.handle.net/10183/87375.
Повний текст джерелаIn this thesis, we present three different applications of Birnbaum-Saunders models. In Chapter 2, we introduce a new nonparametric kernel method for estimating asymmetric densities based on generalized skew-Birnbaum-Saunders distributions. Kernels based on these distributions have the advantage of providing flexibility in the asymmetry and kurtosis levels. In addition, the generalized skew-Birnbaum-Saunders kernel density estimators are boundary bias free and achieve the optimal rate of convergence for the mean integrated squared error of the nonnegative asymmetric kernel density estimators. We carry out a data analysis consisting of two parts. First, we conduct a Monte Carlo simulation study for evaluating the performance of the proposed method. Second, we use this method for estimating the density of three real air pollutant concentration data sets, whose numerical results favor the proposed nonparametric estimators. In Chapter 3, we propose a new family of autoregressive conditional duration models based on scale-mixture Birnbaum-Saunders (SBS) distributions. The Birnbaum-Saunders (BS) distribution is a model that has received considerable attention recently due to its good properties. An extension of this distribution is the class of SBS distributions, which allows (i) several of its good properties to be inherited; (ii) maximum likelihood estimation to be efficiently formulated via the EM algorithm; (iii) a robust estimation procedure to be obtained; among other properties. The autoregressive conditional duration model is the primary family of models to analyze high-frequency financial transaction data. This methodology includes parameter estimation by the EM algorithm, inference for these parameters, the predictive model and a residual analysis. We carry out a Monte Carlo simulation study to evaluate the performance of the proposed methodology. In addition, we assess the practical usefulness of this methodology by using real data of financial transactions from the New York stock exchange. Chapter 4 deals with process capability indices (PCIs), which are tools widely used by companies to determine the quality of a product and the performance of their production processes. These indices were developed for processes whose quality characteristic has a normal distribution. In practice, many of these characteristics do not follow this distribution. In such a case, the PCIs must be modified considering the non-normality. The use of unmodified PCIs can lead to inadequacy results. In order to establish quality policies to solve this inadequacy, data transformation has been proposed, as well as the use of quantiles from non-normal distributions. An asymmetric non-normal distribution which has become very popular in recent times is the Birnbaum-Saunders (BS) distribution. We propose, develop, implement and apply a methodology based on PCIs for the BS distribution. Furthermore, we carry out a simulation study to evaluate the performance of the proposed methodology. This methodology has been implemented in a noncommercial and open source statistical software called R. We apply this methodology to a real data set to illustrate its flexibility and potentiality.
Tencaliec, Patricia. "Developments in statistics applied to hydrometeorology : imputation of streamflow data and semiparametric precipitation modeling." Thesis, Université Grenoble Alpes (ComUE), 2017. http://www.theses.fr/2017GREAM006/document.
Повний текст джерелаPrecipitation and streamflow are the two most important meteorological and hydrological variables when analyzing river watersheds. They provide fundamental insights for water resources management, design, or planning, such as urban water supplies, hydropower, forecast of flood or droughts events, or irrigation systems for agriculture.In this PhD thesis we approach two different problems. The first one originates from the study of observed streamflow data. In order to properly characterize the overall behavior of a watershed, long datasets spanning tens of years are needed. However, the quality of the measurement dataset decreases the further we go back in time, and blocks of data of different lengths are missing from the dataset. These missing intervals represent a loss of information and can cause erroneous summary data interpretation or unreliable scientific analysis.The method that we propose for approaching the problem of streamflow imputation is based on dynamic regression models (DRMs), more specifically, a multiple linear regression with ARIMA residual modeling. Unlike previous studies that address either the inclusion of multiple explanatory variables or the modeling of the residuals from a simple linear regression, the use of DRMs allows to take into account both aspects. We apply this method for reconstructing the data of eight stations situated in the Durance watershed in the south-east of France, each containing daily streamflow measurements over a period of 107 years. By applying the proposed method, we manage to reconstruct the data without making use of additional variables, like other models require. We compare the results of our model with the ones obtained from a complex approach based on analogs coupled to a hydrological model and a nearest-neighbor approach, respectively. In the majority of cases, DRMs show an increased performance when reconstructing missing values blocks of various lengths, in some of the cases ranging up to 20 years.The second problem that we approach in this PhD thesis addresses the statistical modeling of precipitation amounts. The research area regarding this topic is currently very active as the distribution of precipitation is a heavy-tailed one, and at the moment, there is no general method for modeling the entire range of data with high performance. Recently, in order to propose a method that models the full-range precipitation amounts, a new class of distribution called extended generalized Pareto distribution (EGPD) was introduced, specifically with focus on the EGPD models based on parametric families. These models provide an improved performance when compared to previously proposed distributions, however, they lack flexibility in modeling the bulk of the distribution. We want to improve, through, this aspect by proposing in the second part of the thesis, two new models relying on semiparametric methods.The first method that we develop is the transformed kernel estimator based on the EGPD transformation. That is, we propose an estimator obtained by, first, transforming the data with the EGPD cdf, and then, estimating the density of the transformed data by applying a nonparametric kernel density estimator. We compare the results of the proposed method with the ones obtained by applying EGPD on several simulated scenarios, as well as on two precipitation datasets from south-east of France. The results show that the proposed method behaves better than parametric EGPD, the MIAE of the density being in all the cases almost twice as small.A second approach consists of a new model from the general EGPD class, i.e., we consider a semiparametric EGPD based on Bernstein polynomials, more specifically, we use a sparse mixture of beta densities. Once again, we compare our results with the ones obtained by EGPD on both simulated and real datasets. As before, the MIAE of the density is considerably reduced, this effect being even more obvious as the sample size increases
Ahmed, Mohamed Salem. "Contribution à la statistique spatiale et l'analyse de données fonctionnelles." Thesis, Lille 3, 2017. http://www.theses.fr/2017LIL30047/document.
Повний текст джерелаThis thesis is about statistical inference for spatial and/or functional data. Indeed, weare interested in estimation of unknown parameters of some models from random or nonrandom(stratified) samples composed of independent or spatially dependent variables.The specificity of the proposed methods lies in the fact that they take into considerationthe considered sample nature (stratified or spatial sample).We begin by studying data valued in a space of infinite dimension or so-called ”functionaldata”. First, we study a functional binary choice model explored in a case-controlor choice-based sample design context. The specificity of this study is that the proposedmethod takes into account the sampling scheme. We describe a conditional likelihoodfunction under the sampling distribution and a reduction of dimension strategy to definea feasible conditional maximum likelihood estimator of the model. Asymptotic propertiesof the proposed estimates as well as their application to simulated and real data are given.Secondly, we explore a functional linear autoregressive spatial model whose particularityis on the functional nature of the explanatory variable and the structure of the spatialdependence. The estimation procedure consists of reducing the infinite dimension of thefunctional variable and maximizing a quasi-likelihood function. We establish the consistencyand asymptotic normality of the estimator. The usefulness of the methodology isillustrated via simulations and an application to some real data.In the second part of the thesis, we address some estimation and prediction problemsof real random spatial variables. We start by generalizing the k-nearest neighbors method,namely k-NN, to predict a spatial process at non-observed locations using some covariates.The specificity of the proposed k-NN predictor lies in the fact that it is flexible and allowsa number of heterogeneity in the covariate. We establish the almost complete convergencewith rates of the spatial predictor whose performance is ensured by an application oversimulated and environmental data. In addition, we generalize the partially linear probitmodel of independent data to the spatial case. We use a linear process for disturbancesallowing various spatial dependencies and propose a semiparametric estimation approachbased on weighted likelihood and generalized method of moments methods. We establishthe consistency and asymptotic distribution of the proposed estimators and investigate thefinite sample performance of the estimators on simulated data. We end by an applicationof spatial binary choice models to identify UADT (Upper aerodigestive tract) cancer riskfactors in the north region of France which displays the highest rates of such cancerincidence and mortality of the country
Tam, Siu Ming. "Estimation in finite population sampling : robustness and optimality." Phd thesis, 1988. http://hdl.handle.net/1885/10575.
Повний текст джерелаYang, Szu-peng, and 楊思芃. "A class of generalized ridge estimator for high-dimensional linear regression." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/7aw844.
Повний текст джерела國立中央大學
統計研究所
102
In multiple linear regression, the least square estimator is inappropriate for high-dimensional regressors, especially for p≥n. Consider the linear regression model. The generalized ridge estimator has been considered by many authors under the usual p
Yeh, Chi-Kuang. "Optimal regression design under second-order least squares estimator: theory, algorithm and applications." Thesis, 2018. https://dspace.library.uvic.ca//handle/1828/9765.
Повний текст джерелаGraduate
Yzenbrandt, Kai. "Minimax D-optimal designs for regression models with heteroscedastic errors." Thesis, 2021. http://hdl.handle.net/1828/12863.
Повний текст джерелаGraduate
Klička, Petr. "Kalibrační odhady ve výběrových šetřeních." Master's thesis, 2018. http://www.nusl.cz/ntk/nusl-386957.
Повний текст джерелаMundhenk, Philip Henrich. "Integrating remotely sensed data into forest resource inventories." Doctoral thesis, 2014. http://hdl.handle.net/11858/00-1735-0000-0022-5FE6-3.
Повний текст джерелаКниги з теми "Generalised regression estimators"
Linton, Oliver. Edgeworth approximation for generalised minimum contrast estimators in semiparametric regression models. Oxford: Nuffield College, 1992.
Знайти повний текст джерелаFlynn, Robert H. Generalized estimates from streamflow data of annual and seasonal ground-water-recharge rates for drainage basins in New Hampshire. Pembroke, N.H: U.S. Dept. of the Interior, U.S. Geological Survey, 2004.
Знайти повний текст джерелаFlynn, Robert H. Generalized estimates from streamflow data of annual and seasonal ground-water-recharge rates for drainage basins in New Hampshire. Pembroke, N.H: U.S. Dept. of the Interior, U.S. Geological Survey, 2004.
Знайти повний текст джерелаFlynn, Robert H. Generalized estimates from streamflow data of annual and seasonal ground-water-recharge rates for drainage basins in New Hampshire. Pembroke, N.H: U.S. Dept. of the Interior, U.S. Geological Survey, 2004.
Знайти повний текст джерелаFlynn, Robert H. Generalized estimates from streamflow data of annual and seasonal ground-water-recharge rates for drainage basins in New Hampshire. Pembroke, N.H: U.S. Dept. of the Interior, U.S. Geological Survey, 2004.
Знайти повний текст джерелаCardot, Hervé, and Pascal Sarda. Functional Linear Regression. Edited by Frédéric Ferraty and Yves Romain. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199568444.013.2.
Повний текст джерелаD, Tasker Gary, New Hampshire. Dept. of Environmental Services., and Geological Survey (U.S.), eds. Generalized estimates from streamflow data of annual and seasonal ground-water-recharge rates for drainage basins in New Hampshire. Pembroke, N.H: U.S. Dept. of the Interior, U.S. Geological Survey, 2004.
Знайти повний текст джерелаЧастини книг з теми "Generalised regression estimators"
Bartels, Robert, and Denzil G. Fiebig. "Efficiency of Alternative Estimators in Generalized Seemingly Unrelated Regression Models." In Contributions to Consumer Demand and Econometrics, 125–39. London: Palgrave Macmillan UK, 1992. http://dx.doi.org/10.1007/978-1-349-12221-9_7.
Повний текст джерелаTaylan, Pakize, and Gerhard Wilhelm Weber. "C-LASSO Estimator for Generalized Additive Logistic Regression Based on B-Spline." In Data Science and Digital Business, 173–90. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-95651-0_10.
Повний текст джерелаSengupta, Ramprasad. "Crime, Inequality, and Poverty." In Entropy Law, Sustainability, and Third Industrial Revolution, 70–100. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780190121143.003.0004.
Повний текст джерелаKiziltan, Mustafa. "The Effects of Population Aging and Life Expectancy on Economic Growth." In Advances in Human Services and Public Health, 97–118. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-7327-3.ch007.
Повний текст джерелаAndrews, Martyn, Alastair R. Hall, Rabeya Khatoon, and James Lincoln. "Info-metric Methods for the Estimation of Models with Group-Specific Moment Conditions." In Advances in Info-Metrics, 349–84. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780190636685.003.0013.
Повний текст джерелаТези доповідей конференцій з теми "Generalised regression estimators"
Kolansky, Jeremy, and Corina Sandu. "Generalized Polynomial Chaos-Based Extended Kalman Filter: Improvement and Expansion." In ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/detc2013-12082.
Повний текст джерелаHage, Ilige S., Charbel Y. Seif, Ré-Mi Hage, and Ramsey F. Hamade. "A Verified Non-Linear Regression Model for Elastic Stiffness Estimates of Finite Composite Domains Considering Combined Effects of Volume Fractions, Shapes, Orientations, Locations, and Number of Multiple Inclusions." In ASME 2018 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/imece2018-86231.
Повний текст джерелаVanem, Erik, and Sam-Erik Walker. "Time Series Analysis of Significant Wave Height Data for Identification of Trends in the Ocean Wave Climate." In ASME 2013 32nd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/omae2013-10024.
Повний текст джерелаZhou, Peng, Ligang Lu, Huiyan Sang, and Birol Dindoruk. "Application of Machine Learning Methods to Well Completion Optimization: Problems with Groups of Interactive Inputs." In SPE Annual Technical Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/206174-ms.
Повний текст джерелаBanerjee, Ashis Gopal, Walter Yund, Dan Yang, Peter Koudal, John Carbone, and Joseph Salvo. "A Hybrid Statistical Method for Accurate Prediction of Supplier Delivery Times of Aircraft Engine Parts." In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-47605.
Повний текст джерелаRandell, David, Elena Zanini, Michael Vogel, Kevin Ewans, and Philip Jonathan. "Omnidirectional Return Values for Storm Severity From Directional Extreme Value Models: The Effect of Physical Environment and Sample Size." In ASME 2014 33rd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/omae2014-23156.
Повний текст джерелаЗвіти організацій з теми "Generalised regression estimators"
Over, Thomas, Riki Saito, Andrea Veilleux, Padraic O’Shea, Jennifer Sharpe, David Soong, and Audrey Ishii. Estimation of Peak Discharge Quantiles for Selected Annual Exceedance Probabilities in Northeastern Illinois. Illinois Center for Transportation, June 2016. http://dx.doi.org/10.36501/0197-9191/16-014.
Повний текст джерела