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Littérature scientifique sur le sujet « Complementary cumulative distribution function »

Auteur : Grafiati

Publié le 4 juin 2021

Mis à jour le 1 février 2022

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Articles de revues sur le sujet "Complementary cumulative distribution function"

Kaur, Parneet. « Complementary Cumulative Distribution Function for Performance Analysis of OFDM Signals ». IOSR Journal of Electronics and Communication Engineering 2, n^o 5 (2012) : 05–07. http://dx.doi.org/10.9790/2834-0250507.

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Kim, Bongsong. « How to Reveal Magnitude of Gene Signals : Hierarchical Hypergeometric Complementary Cumulative Distribution Function ». Evolutionary Bioinformatics 14 (janvier 2018) : 117693431879735. http://dx.doi.org/10.1177/1176934318797352.

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Iyit, Neslihan. « Modelling world energy security data from multinomial distribution by generalized linear model under different cumulative link functions ». Open Chemistry 16, n^o 1 (30 avril 2018) : 377–85. http://dx.doi.org/10.1515/chem-2018-0053.

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AbstractEnergy securityis one of the major components of energy sustainability in the world’s energy performance. In this study,energy securityis taken as an ordinal response variable coming from the multinomial distribution with the energy grade levelsA,B,C, andD. Thereafter, the worldenergy securitydata is tried to be statistically modelled by usinggeneralized linear model (GLM)approach for the ordinal response variable under different cumulative link functions. The cumulative link functions comparatively used in this study are cumulative logit, cumulative probit, cumulative complementary log-log, cumulative Cauchit, and cumulative negative log-log. In order to avoid a multicollinearity problem in the data structure, principal component analysis (PCA) technique is integrated with theGLMapproach for the ordinal response variable. In this study, statistically, the importance of determining the best cumulative link function on the accuracy of parameter estimates, confidence intervals, and hypothesis tests in theGLMfor the multinomially distributed response variable is highlighted. In terms of energy evaluation, by usingcumulative logitas the best cumulative link function,energy sources consumptions,electricity productions from nuclear energy,natural gas,oil,coal,and hydroelectric,energy use per capita and energy importsare found to have statistically significant effects onenergy securityin the world’s energy performance.

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Sato, Aki Hiro. « A Method to Quantify Risks of Financial Assets : An Empirical Analysis of Japanese Security Prices ». Advanced Materials Research 452-453 (janvier 2012) : 469–73. http://dx.doi.org/10.4028/www.scientific.net/amr.452-453.469.

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This study investigates unconditional distributions of daily log-returns of Japanese security prices from a comprehensive point of view. The purpose of this article is to estimate a risk distribution of stocks in terms of Value-at-Risk (VaR) in order to select low risk securities from many securities. Daily log-return time series of 1,340 Japanese companies listed on the first section of Tokyo Stock Exchange are examined during the last one decade. I develop a method to estimate VaR by both the maximum likelihood estimation procedure under a q-Gaussian assumption and analytical form of its cumulative distribution function. It is confirmed that they are fitted to q-Gaussian distributions (Student t-distributions) with Kolmogorov-Smirnov test. It is found that the complementary cumulative distribution function of VaR has a power-law tail with its characteristic exponent depending on values of the VaR percentile.

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Schaeben, Helmut. « Non-Parametric Comparison of Crystallographic Orientation Distributions ». Materials Science Forum 1016 (janvier 2021) : 1258–63. http://dx.doi.org/10.4028/www.scientific.net/msf.1016.1258.

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Revisiting a spiral design for X-ray pole figure measurementsand a symbolic definition of a cumulative crystallographic orientation distributiona one-dimensional deterministic approximately uniform sequential design is appliedto evaluate and cumulate a given orientation density function resulting in a properly definedcumulative crystallographic orientation distribution.It provides a complementary means to compare distributionsin terms of graphs and the Kolomogorov-Smirnov distance.

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Chesneau, Christophe. « Study of a unit power-logarithmic distribution ». Open Journal of Mathematical Sciences 5, n^o 1 (24 mai 2021) : 218–35. http://dx.doi.org/10.30538/oms2021.0159.

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This article proposes a new unit distribution based on the power-logarithmic scheme. The corresponding cumulative distribution function is defined by a special ratio of power and logarithmic functions that is dependent on one parameter. We show that this function benefits from great flexibility characterized by a large selection of convex and concave shapes. The other key functions are determined and studied. In particular, we show that the probability density function may take on different decreasing or U shapes, and the hazard rate function has a wide panel of U shapes. These functional capabilities are rare for a one-parameter unit distribution. In addition, we prove certain stochastic order results, provide the expression of the quantile function via the Lambert function, some interesting distributional results, and give simple expressions for the ordinary moments, mean, variance, skewness, kurtosis, moment generating function and incomplete moments. Subsequently, a basic statistical approach is described, to show how the new distribution can be applied in a data analysis scenario. Finally, complementary mathematical findings are presented, yielding new integrals linked to the Euler constant via some well-known moments properties.

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Hassan, Amal, Salwa Assar et Kareem Ali. « The complementary Poisson-Lindley class of distributions ». International Journal of Advanced Statistics and Probability 3, n^o 2 (29 juin 2015) : 146. http://dx.doi.org/10.14419/ijasp.v3i2.4624.

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<p>This paper proposed a new general class of continuous lifetime distributions, which is a complementary to the Poisson-Lindley family proposed by Asgharzadeh et al. [3]. The new class is derived by compounding the maximum of a random number of independent and identically continuous distributed random variables, and Poisson-Lindley distribution. Several properties of the proposed class are discussed, including a formal proof of probability density, cumulative distribution, and reliability and hazard rate functions. The unknown parameters are estimated by the maximum likelihood method and the Fisher’s information matrix elements are determined. Some sub-models of this class are investigated and studied in some details. Finally, a real data set is analyzed to illustrate the performance of new distributions.</p>

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Walsh, Anthony J., John A. O’Dowd, Vivian M. Bessler, Kai Shi, Frank Smyth, James M. Dailey, Bryan Kelleher, Liam P. Barry et Andrew D. Ellis. « Characterization of time-resolved laser differential phase using 3D complementary cumulative distribution functions ». Optics Letters 37, n^o 10 (15 mai 2012) : 1769. http://dx.doi.org/10.1364/ol.37.001769.

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Prasetyo, Rindang Bangun, Heri Kuswanto, Nur Iriawan et Brodjol Sutijo Suprih Ulama. « Binomial Regression Models with a Flexible Generalized Logit Link Function ». Symmetry 12, n^o 2 (2 février 2020) : 221. http://dx.doi.org/10.3390/sym12020221.

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In binomial regression, a link function is used to join the linear predictor variables and the expectation of the response variable. This paper proposes a flexible link function from a new class of generalized logistic distribution, namely a flexible generalized logit (glogit) link. This approach considers both symmetric and asymmetric models, including the cases of lighter and heavier tails, as compared to standard logistic. The glogit is created from the inverse cumulative distribution function of the exponentiated-exponential logistic (EEL) distribution. Using a Bayesian framework, we conduct a simulation study to investigate the model performance compared to the most commonly used link functions, e.g., logit, probit, and complementary log–log. Furthermore, we compared the proposed model with several other asymmetric models using two previously published datasets. The results show that the proposed model outperforms the existing ones and provides flexibility fitting the experimental dataset. Another attractive aspect of the model are analytically tractable and can be easily implemented under a Bayesian approach.

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Helton, J. C. « Probability, conditional probability and complementary cumulative distribution functions in performance assessment for radioactive waste disposal ». Reliability Engineering & ; System Safety 54, n^o 2-3 (novembre 1996) : 145–63. http://dx.doi.org/10.1016/s0951-8320(96)00072-5.

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Thèses sur le sujet "Complementary cumulative distribution function"

Oltean, Elvis. « Modelling income, wealth, and expenditure data by use of Econophysics ». Thesis, Loughborough University, 2016. https://dspace.lboro.ac.uk/2134/20203.

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In the present paper, we identify several distributions from Physics and study their applicability to phenomena such as distribution of income, wealth, and expenditure. Firstly, we apply logistic distribution to these data and we find that it fits very well the annual data for the entire income interval including for upper income segment of population. Secondly, we apply Fermi-Dirac distribution to these data. We seek to explain possible correlations and analogies between economic systems and statistical thermodynamics systems. We try to explain their behaviour and properties when we correlate physical variables with macroeconomic aggregates and indicators. Then we draw some analogies between parameters of the Fermi-Dirac distribution and macroeconomic variables. Thirdly, as complex systems are modelled using polynomial distributions, we apply polynomials to the annual sets of data and we find that it fits very well also the entire income interval. Fourthly, we develop a new methodology to approach dynamically the income, wealth, and expenditure distribution similarly with dynamical complex systems. This methodology was applied to different time intervals consisting of consecutive years up to 35 years. Finally, we develop a mathematical model based on a Hamiltonian that maximises utility function applied to Ramsey model using Fermi-Dirac and polynomial utility functions. We find some theoretical connections with time preference theory. We apply these distributions to a large pool of data from countries with different levels of development, using different methods for calculation of income, wealth, and expenditure.

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BAIG, CLEMENT RANJITH ANTHIKKAD &amp IRFAN AHMED. « PERFORMANCE ENHANCEMENT OF OFDM IN PAPR REDUCTION USING NEW COMPANDING TRANSFORM AND ADAPTIVE AC EXTENSION ALGORITHM FOR NEXT GENERATION NETWORKSPERFORMANCE ENHANCEMENT OF OFDM IN PAPR REDUCTION USING NEW COMPANDING TRANSFORM AND ADAPTIVE AC EXTENSION ALGORITHM FOR NEXT GENERATION NETWORKS ». Thesis, Blekinge Tekniska Högskola, Sektionen för ingenjörsvetenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-6011.

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This paper presents a new hybrid PAPR reduction technique for the OFDM signal, which combines a multiple symbol representations method with a signal clipping method. The clipping method is a nonlinear PAPR reduction scheme, where the amplitude of the signal is limited to a given threshold. Considering the fact that the signal must be interpolated before A/D conversion, a variety of clipping methods has been proposed. Some methods suggest the clipping before interpolation, having the disadvantage of the peaks re-growth. Other methods contributed that the clipping after interpolation, having the disadvantage of out-of-band power production. In order to overcome this problem different filtering techniques have been proposed. Filtering can also cause peak re-growth, but less than the clipping before interpolation. Another clipping technique supposes that only subcarriers having the highest phase difference between the original signal and its clipped variant will be changed. This is the case of the partial clipping method. To further reduce the PAPR, the dynamic of the clipped signal can be compressed. Linear methods like partial transmit sequence or selective mapping has been proposed for the reduction of PAPR as well. Another PAPR reduction method is the tone reservation. It uses tones on which no data is sent to reduce the transmitted signal peaks. Derivatives of this method with lower computation complexity and improved performance have been proposed: One-Tone One-Peak and one by-one iteration. A similar PAPR reduction method is the multiple symbol representations, where alternative signalling points are used to represent one symbol. The simulation results highlight the advantages of the proposed PAPR reduction method.
The proposed technique namely Adaptive Active Constellation Extension (Adaptive ACE) Algorithm reduced the high Peak-to-Average Power Ratio (PAPR) of the Orthogonal Frequency Division Multiplexing (OFDM) systems. The Peak-to-Average Power Ratio (PAPR) is equal to 6.8 dB for the target clipping ratios of 4 dB, 2 dB and 0 dB by using Adaptive Active Constellation Extension (Adaptive ACE) Algorithm. Thus, the minimum PAPR can be achieved for low target clipping ratios. The Signal-to-Noise Ratio (SNR) of the Orthogonal Frequency Division Multiplexing (OFDM) signal obtained by the Adaptive Active Constellation Extension (Adaptive ACE) algorithm is equal to 1.2 dB at a Bit Error Rate (BER) of 10-0..4 for different constellation orders like 4-Quadrature Amplitude Modulation (4-QAM), 16-Quadrature Amplitude Modulation (16-QAM) and 64-Quadrature Amplitude Modulation (16-QAM). Here, the Bit Error Rate of 10-0.4 or 0.398, that means a total of 398-bits are in error when 1000-bits are transmitted via a communication channel or approximately 4-bits are in error when 10-bits are transmitted via a communication channel, which is high when compared to that of the original Orthogonal Frequency Division Multiplexing (OFDM) signal. The other problems faced by the Adaptive Active Constellation Extension (Adaptive ACE) algorithm are Out-of-Band Interference (OBI) and peak regrowth. Here, the Out-of-Band Interference (OBI) is a form of noise or an unwanted signal, which is caused when the original Orthogonal Frequency Division Multiplexing (OFDM) signal is clipped for reducing the peak signals which are outside of the predetermined area and the peak regrowth is obtained after filtering the clipped signal. The peak regrowth results to, increase in the computational time and computational complexity. In this paper, we have proposed a PAPR reduction scheme to improve the bit error rate performance by applying companding transform technique. Hence, 1-1.5 dB reduction in PAPR with this Non-companding technique is achieved. In Future, We can accept to implement the same on Rician and Rayleigh channels.
Clement Ranjith Anthikkad (E-mail: clement.ranjith@gmail.com / clan11@bth.se) & Irfan Ahmed Baig (E-mail: baig.irfanahmed@gmail.com / ir-a11@bth.se )

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Liu, Xuecheng 1963. « Nonparametric maximum likelihood estimation of the cumulative distribution function with multivariate interval censored data : computation, identifiability and bounds ». Thesis, McGill University, 2002. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=79036.

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This thesis addresses nonparametric maximal likelihood (NPML) estimation of the cumulative distribution function (CDF) given multivariate interval censored data (MILD). The methodology consists in applying graph theory to the intersection graph of censored data. The maximal cliques of this graph and their real representations contain all the information needed to find NPML estimates (NPMLE). In this thesis, a new algorithm to determine the maximal cliques of an MICD set is introduced. The concepts of diameter and semi-diameter of the polytope formed by all NPMLEs are introduced and simulation to investigate the properties of the non-uniqueness polytope of the CDF NPMLEs for bivariate censored data is described. Also, an a priori bounding technique for the total mass attributed to a set of maximal cliques by a self-consistent estimate of the CDF (including the NPMLE) is presented.

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Forgo, Vincent Z. Mr. « A Distribution of the First Order Statistic When the Sample Size is Random ». Digital Commons @ East Tennessee State University, 2017. https://dc.etsu.edu/etd/3181.

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Statistical distributions also known as probability distributions are used to model a random experiment. Probability distributions consist of probability density functions (pdf) and cumulative density functions (cdf). Probability distributions are widely used in the area of engineering, actuarial science, computer science, biological science, physics, and other applicable areas of study. Statistics are used to draw conclusions about the population through probability models. Sample statistics such as the minimum, first quartile, median, third quartile, and maximum, referred to as the five-number summary, are examples of order statistics. The minimum and maximum observations are important in extreme value theory. This paper will focus on the probability distribution of the minimum observation, also known as the first order statistic, when the sample size is random.

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Jeisman, Joseph Ian. « Estimation of the parameters of stochastic differential equations ». Queensland University of Technology, 2006. http://eprints.qut.edu.au/16205/.

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Stochastic di®erential equations (SDEs) are　central to much of modern finance theory and have been widely used to model the behaviour of key variables such as the　instantaneous short-term interest rate, asset prices, asset returns and their volatility.　The explanatory and/or predictive power of these models depends crucially on the particularisation of the model SDE(s) to real data through the choice of values for their parameters. In econometrics, optimal parameter estimates are generally considered to　be those that maximise the likelihood of the sample. In the context of the estimation of the parameters of SDEs, however, a closed-form expression for the likelihood　function is rarely available and hence exact maximum-likelihood (EML) estimation is usually infeasible. The key research problem examined in this thesis is the development of generic, accurate and computationally feasible estimation procedures based on the　ML principle, that can be implemented in the absence of a closed-form expression for　the likelihood function. The overall recommendation to come out of the thesis is that　an estimation procedure based on the finite-element solution of a reformulation of the Fokker-Planck equation in terms of the transitional cumulative distribution function(CDF) provides the best balance across all of the desired characteristics. The recommended approach involves the use of an interpolation technique proposed in this thesis which greatly reduces the required computational effort.

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Ericok, Ozlen. « Uncertainty Assessment In Reserv Estimation Of A Naturally Fractured Reservoir ». Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/2/12605713/index.pdf.

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ABSTRACT UNCERTAINTY ASSESSMENT IN RESERVE ESTIMATION OF A NATURALLY FRACTURED RESERVOIR ERIÇ
OK, Ö
zlen M.S., Department of Petroleum and Natural Gas Engineering Supervisor : Prof. Dr. Fevzi GÜ
MRAH December 2004, 169 pages Reservoir performance prediction and reserve estimation depend on various petrophysical parameters which have uncertainties due to available technology. For a proper and economical field development, these parameters must be determined by taking into consideration their uncertainty level and probable data ranges. For implementing uncertainty assessment on estimation of original oil in place (OOIP) of a field, a naturally fractured carbonate field, Field-A, is chosen to work with. Since field information is obtained by drilling and testing wells throughout the field, uncertainty in true ranges of reservoir parameters evolve due to impossibility of drilling every location on an area. This study is based on defining the probability distribution of uncertain variables in reserve estimation and evaluating probable reserve amount by using Monte Carlo simulation method. Probabilistic reserve estimation gives the whole range of probable v original oil in place amount of a field. The results are given by their likelyhood of occurance as P10, P50 and P90 reserves in summary. In the study, Field-A reserves at Southeast of Turkey are estimated by probabilistic methods for three producing zones
Karabogaz Formation, Kbb-C Member of Karababa formation and Derdere Formation. Probability density function of petrophysical parameters are evaluated as inputs in volumetric reserve estimation method and probable reserves are calculated by @Risk software program that is used for implementing Monte Carlo method. Outcomes of the simulation showed that Field-A has P50 reserves as 11.2 MMstb in matrix and 2.0 MMstb in fracture of Karabogaz Formation, 15.7 MMstb in matrix and 3.7 MMstb in fracture of Kbb-C Member and 10.6 MMstb in matrix and 1.6 MMstb in fracture of Derdere Formation. Sensitivity analysis of the inputs showed that matrix porosity, net thickness and fracture porosity are significant in Karabogaz Formation and Kbb-C Member reserve estimation while water saturation and fracture porosity are most significant in estimation of Derdere Formation reserves.

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Cunha, Lucas Santana da. « Modelos não lineares resultantes da soma de regressões lineares ponderadas por funções distribuição acumulada ». Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/11/11134/tde-04052016-100308/.

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Os controladores eletrônicos de pulverização visam minimizar a variação das taxas de insumos aplicadas no campo. Eles fazem parte de um sistema de controle, e permitem a compensação da variação de velocidade de deslocamento do pulverizador durante a operação. Há vários tipos de controladores eletrônicos de pulverização disponíveis no mercado e uma das formas de selecionar qual o mais eficiente nas mesmas condições, ou seja, em um mesmo sistema de controle, é quantificar o tempo de resposta do sistema para cada controlador específico. O objetivo desse trabalho foi estimar os tempos de resposta para mudanças de velocidade de um sistema eletrônico de pulverização via modelos de regressão não lineares, estes, resultantes da soma de regressões lineares ponderadas por funções distribuição acumulada. Os dados foram obtidos no Laboratório de Tecnologia de Aplicação, localizado no Departamento de Engenharia de Biossistemas da Escola Superior de Agricultura \"Luiz de Queiroz\", Universidade de São Paulo, no município de Piracicaba, São Paulo, Brasil. Os modelos utilizados foram o logístico e de Gompertz, que resultam de uma soma ponderada de duas regressões lineares constantes com peso dado pela função distribuição acumulada logística e Gumbell, respectivamente. Reparametrizações foram propostas para inclusão do tempo de resposta do sistema de controle nos modelos, com o objetivo de melhorar a interpretação e inferência estatística dos mesmos. Foi proposto também um modelo de regressão não linear difásico que resulta da soma ponderada de regressões lineares constantes com peso dado pela função distribuição acumulada Cauchy seno hiperbólico exponencial. Um estudo de simulação foi feito, utilizando a metodologia de Monte Carlo, para avaliar as estimativas de máxima verossimilhança dos parâmetros do modelo.
The electronic controllers spray aimed at minimizing the variation of inputs rates applied in the field. They are part of a control system, and allow for compensation for variation spray travel speed during operation. There are several types of electronic spray controllers on the market and one way to select which more efficient under the same conditions, ie in the same system of control, is to quantify the system response time for each specific driver. The objective of this study was to estimate the response times for changes in speed of an electronic spraying system via nonlinear regression models, these resulting from the sum of weighted linear regressions for cumulative distribution functions. Data were obtained on the Application Technology Laboratory, located in the Department of Biosystems Engineering from College of Agriculture \"Luiz de Queiroz\", University of Sao Paulo, in Piracicaba, Sao Paulo, Brazil. The models used were the logistic and Gompertz, resulting from a weighted sum of two constant linear regressions with weight given by the cumulative distribution function logistics and Gumbell respectively. Reparametrization been proposed for inclusion in the control system response time models, in order to improve the statistical interpretation and inference of the same. It has also been proposed a non-linear regression model two-phase which is the weighted sum of constant linear regressions weight given by a cumulative distribution function exponential hyperbolic sine Cauchy in which a simulation study was conducted using the methodology of Monte Carlo to evaluating the maximum likelihood estimates of the model parameters.

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Bothenna, Hasitha Imantha. « Approximation of Information Rates in Non-Coherent MISO wireless channels with finite input signals ». University of Akron / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=akron1516369758012866.

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Dhuness, Kahesh. « An offset modulation method used to control the PAPR of an OFDM transmission ». Thesis, University of Pretoria, 2012. http://hdl.handle.net/2263/27258.

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Orthogonal frequency division multiplexing (OFDM) has become a very popular method for high-data-rate communication. However, it is well known that OFDM is plagued by a large peak-to-average power ratio (PAPR) problem. This high PAPR results in overdesigned power amplifiers, which amongst other things leads to inefficient amplifier usage, which is undesirable. Various methods have been recommended to reduce the PAPR of an OFDM transmission; however, all these methods result in a number of drawbacks. In this thesis, a novel method called offset modulation (OM-OFDM) is proposed to control the PAPR of an OFDM signal. The proposed OM-OFDM method does not result in a number of the drawbacks being experienced by current methods in the field. The theoretical bandwidth occupancy and theoretical bit error rate (BER) expression for an OM-OFDM transmission is derived. A newly applied power performance decision metric is also introduced, which can be utilised throughout the PAPR field, in order to compare various methods. The proposed OM-OFDM method appears to be similar to a well-known constant envelope OFDM (CE-OFDM) transmission. The modulation, structural and performance differences between an OM-OFDM and a CE-OFDM method are discussed. By applying the power performance decision metric, the OM-OFDM method is shown to offer significant performance gains when compared to CE-OFDM and traditional OFDM transmissions. In addition, the OM-OFDM method is able to accurately control the PAPR of a transmission for a targeted BER. By applying the power performance decision metric and complementary cumulative distribution function (CCDF), the proposed OM-OFDM method is shown to offer further performance gains when compared to existing PAPR methods, under frequency selective fading conditions. In this thesis, the OM-OFDM method has been combined with an existing active constellation extended (ACE) PAPR reduction method. To introduce a novel method called offset modulation with active constellation extension (OM-ACE), to control the PAPR of an OFDM signal. The theoretical BER expression for an OM-ACE transmission is presented and validated. Thereafter, by applying the decision metric and CCDF, the OM-ACE method is shown to offer performance improvements when compared to various PAPR methods. The use of OM-OFDM for cognitive radio applications is also investigated. Cognitive radio applications require transmissions that are easily detectable. The detection characteristics of an OM-OFDM and OFDM transmission are studied by using receiver operating characteristic curves. A derivation of a simplified theoretical closed-form expression, which relates the probability of a missed detection to the probability of a false alarm, for an unknown deterministic signal, at various signal-to-noise ratio (SNR) values is derived and validated. Previous expressions have been derived, which relate the probability of a missed detection to the probability of a false alarm. However, they have not been presented in such a generic closed-form expression that can be used for any unknown deterministic signal (for instance OFDM and OM-OFDM). Thereafter, an examination of the spectrum characteristics of an OM-OFDM transmission indicates its attractive detection characteristics. The proposed OM-OFDM method is further shown to operate at a significantly lower SNR value than an OFDM transmission, while still offering better detection characteristics than that of an OFDM transmission under Rician, Rayleigh and frequency selective fading channel conditions. In addition to its attractive PAPR properties, OM-OFDM also offers good detection characteristics for cognitive radio applications. These aspects make OM-OFDM a promising candidate for future deployment.
Thesis (PhD)--University of Pretoria, 2012.
Electrical, Electronic and Computer Engineering
unrestricted

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Ahmad, Shafiq, et Shafiq ahmad@rmit edu au. « Process capability assessment for univariate and multivariate non-normal correlated quality characteristics ». RMIT University. Mathematical and Geospatial Sciences, 2009. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20091127.121556.

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In today's competitive business and industrial environment, it is becoming more crucial than ever to assess precisely process losses due to non-compliance to customer specifications. To assess these losses, industry is extensively using Process Capability Indices for performance evaluation of their processes. Determination of the performance capability of a stable process using the standard process capability indices such as and requires that the underlying quality characteristics data follow a normal distribution. However it is an undisputed fact that real processes very often produce non-normal quality characteristics data and also these quality characteristics are very often correlated with each other. For such non-normal and correlated multivariate quality characteristics, application of standard capability measures using conventional methods can lead to erroneous results. The research undertaken in this PhD thesis presents several capability assessment methods to estimate more precisely and accurately process performances based on univariate as well as multivariate quality characteristics. The proposed capability assessment methods also take into account the correlation, variance and covariance as well as non-normality issues of the quality characteristics data. A comprehensive review of the existing univariate and multivariate PCI estimations have been provided. We have proposed fitting Burr XII distributions to continuous positively skewed data. The proportion of nonconformance (PNC) for process measurements is then obtained by using Burr XII distribution, rather than through the traditional practice of fitting different distributions to real data. Maximum likelihood method is deployed to improve the accuracy of PCI based on Burr XII distribution. Different numerical methods such as Evolutionary and Simulated Annealing algorithms are deployed to estimate parameters of the fitted Burr XII distribution. We have also introduced new transformation method called Best Root Transformation approach to transform non-normal data to normal data and then apply the traditional PCI method to estimate the proportion of non-conforming data. Another approach which has been introduced in this thesis is to deploy Burr XII cumulative density function for PCI estimation using Cumulative Density Function technique. The proposed approach is in contrast to the approach adopted in the research literature i.e. use of best-fitting density function from known distributions to non-normal data for PCI estimation. The proposed CDF technique has also been extended to estimate process capability for bivariate non-normal quality characteristics data. A new multivariate capability index based on the Generalized Covariance Distance (GCD) is proposed. This novel approach reduces the dimension of multivariate data by transforming correlated variables into univariate ones through a metric function. This approach evaluates process capability for correlated non-normal multivariate quality characteristics. Unlike the Geometric Distance approach, GCD approach takes into account the scaling effect of the variance-covariance matrix and produces a Covariance Distance variable that is based on the Mahanalobis distance. Another novelty introduced in this research is to approximate the distribution of these distances by a Burr XII distribution and then estimate its parameters using numerical search algorithm. It is demonstrates that the proportion of nonconformance (PNC) using proposed method is very close to the actual PNC value.

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Livres sur le sujet "Complementary cumulative distribution function"

Wildman, Valerie Jean. Estimating effective area surveyed with the cumulative distribution function. Corvallis, Or : Dept. of Statistics, Oregon State University, 1985.

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Ma, Xiaofang. Computation of the probability density function and the cumulative distribution function of the generalized gamma variance model. Ottawa : National Library of Canada, 2002.

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Chapitres de livres sur le sujet "Complementary cumulative distribution function"

Gooch, Jan W. « Cumulative Distribution Function ». Dans Encyclopedic Dictionary of Polymers, 980. New York, NY : Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-6247-8_15210.

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Nguyen, Hung T., et Gerald S. Rogers. « The Cumulative Distribution Function ». Dans Springer Texts in Statistics, 201–7. New York, NY : Springer New York, 1989. http://dx.doi.org/10.1007/978-1-4612-1013-9_24.

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Kokoska, Stephen, et Christopher Nevison. « The Binomial Cumulative Distribution Function ». Dans Springer Texts in Statistics, 50–51. New York, NY : Springer New York, 1989. http://dx.doi.org/10.1007/978-1-4613-9629-1_5.

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Kokoska, Stephen, et Christopher Nevison. « The Poisson Cumulative Distribution Function ». Dans Springer Texts in Statistics, 52–54. New York, NY : Springer New York, 1989. http://dx.doi.org/10.1007/978-1-4613-9629-1_6.

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Zhu, Jun, S. N. Lahiri et Noel Cressie. « Asymptotic Distribution of the Empirical Cumulative Distribution Function Predictor under Nonstationarity ». Dans Spatial Statistics : Methodological Aspects and Applications, 1–20. New York, NY : Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4613-0147-9_1.

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Kokoska, Stephen, et Christopher Nevison. « Cumulative Distribution Function for the Standard Normal Random Variable ». Dans Springer Texts in Statistics, 55–56. New York, NY : Springer New York, 1989. http://dx.doi.org/10.1007/978-1-4613-9629-1_7.

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Lima, Roberta, et Rubens Sampaio. « Uncertainty Quantification and Cumulative Distribution Function : How are they Related ? » Dans Springer Proceedings in Mathematics & ; Statistics, 253–60. Cham : Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91143-4_24.

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Zhang, Juan, et John E. Kolassa. « A comparison of the accuracy of saddlepoint conditional cumulative distribution function approximations ». Dans Complex Datasets and Inverse Problems, 250–59. Beachwood, Ohio, USA : Institute of Mathematical Statistics, 2007. http://dx.doi.org/10.1214/074921707000000193.

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Liu, Xuecheng, et Shoumei Li. « Cumulative Distribution Function Estimation with Fuzzy Data : Some Estimators and Further Problems ». Dans Synergies of Soft Computing and Statistics for Intelligent Data Analysis, 83–91. Berlin, Heidelberg : Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-33042-1_10.

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Galgana, Rigel, Cengke Shi, Amy Greenwald et Takehiro Oyakawa. « A Dynamic Program for Computing the Joint Cumulative Distribution Function of Order Statistics ». Dans SIAM Conference on Applied and Computational Discrete Algorithms (ACDA21), 160–70. Philadelphia, PA : Society for Industrial and Applied Mathematics, 2021. http://dx.doi.org/10.1137/1.9781611976830.15.

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Actes de conférences sur le sujet "Complementary cumulative distribution function"

Zhu, Bingcheng, Zhaoquan Zeng et Julian Cheng. « Arbitrarily tight bounds on cumulative distribution function of Beckmann distribution ». Dans 2017 International Conference on Computing, Networking and Communications (ICNC). IEEE, 2017. http://dx.doi.org/10.1109/iccnc.2017.7876099.

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Tanyer, Suleyman Gokhun. « The Cumulative Distribution Function for a finite data set ». Dans 2012 20th Signal Processing and Communications Applications Conference (SIU). IEEE, 2012. http://dx.doi.org/10.1109/siu.2012.6204462.

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Dash, Jatindra K., Sudipta Mukhopadhyay et Niranjan Khandelwal. « Complementary cumulative precision distribution : a new graphical metric for medical image retrieval system ». Dans SPIE Medical Imaging, sous la direction de Claudia R. Mello-Thoms et Matthew A. Kupinski. SPIE, 2014. http://dx.doi.org/10.1117/12.2043156.

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Mayhew, Gregory L. « Cumulative distribution function for order 7 de Bruijn weight classes ». Dans 2009 IEEE Aerospace conference. IEEE, 2009. http://dx.doi.org/10.1109/aero.2009.4839405.

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Krug, Gregory, et Janusz Madejski. « Improving track condition by application of Quasi Cumulative Distribution Function (QCDF) ». Dans Fifth International Conference on Road and Rail Infrastructure. University of Zagreb Faculty of Civil Engineering, 2018. http://dx.doi.org/10.5592/co/cetra.2018.749.

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Jang, Seul Ki, Yoon-Gyoo Lee, Gyoung-Soo Park et Choon-Woo Kim. « Content-dependent contrast enhancement for displays based on cumulative distribution function ». Dans IS&T/SPIE Electronic Imaging, sous la direction de Reiner Eschbach, Gabriel G. Marcu et Alessandro Rizzi. SPIE, 2013. http://dx.doi.org/10.1117/12.2007236.

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Malinova, Anna, Olga Rahneva, Nikolay Pavlov, Angel Golev et Vesselin Kyurkchiev. « A look at the Garima cumulative distribution function some related problems ». Dans SEVENTH INTERNATIONAL CONFERENCE ON NEW TRENDS IN THE APPLICATIONS OF DIFFERENTIAL EQUATIONS IN SCIENCES (NTADES 2020). AIP Publishing, 2021. http://dx.doi.org/10.1063/5.0040121.

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Lee, Jongmin, Pingping Zhu et Jose C. Principe. « A parameter-free kernel design based on cumulative distribution function for correntropy ». Dans 2013 International Joint Conference on Neural Networks (IJCNN 2013 - Dallas). IEEE, 2013. http://dx.doi.org/10.1109/ijcnn.2013.6707021.

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Yelmanov, Sergei, Olena Hranovska et Yuriy Romanyshyn. « Image Enhancement Technique based on Power-Law Transformation of Cumulative Distribution Function ». Dans 2019 3rd International Conference on Advanced Information and Communications Technologies (AICT). IEEE, 2019. http://dx.doi.org/10.1109/aiact.2019.8847876.

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Manjunath, K. N., et U. C. Niranjan. « Linear Models of Cumulative Distribution Function for Content based Medical Image Retrieval ». Dans 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference. IEEE, 2005. http://dx.doi.org/10.1109/iembs.2005.1615981.

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Rapports d'organisations sur le sujet "Complementary cumulative distribution function"

Helton, J. C. Probability, conditional probability and complementary cumulative distribution functions in performance assessment for radioactive waste disposal. Office of Scientific and Technical Information (OSTI), mars 1996. http://dx.doi.org/10.2172/231952.

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Helton, J. C., et A. W. Shiver. A Monte Carlo procedure for the construction of complementary cumulative distribution functions for comparison with the EPA release limits for radioactive waste disposal. Office of Scientific and Technical Information (OSTI), octobre 1994. http://dx.doi.org/10.2172/27828.

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