Results 31 to 40 of about 41,346 (266)
Modified Ridge Logistic Estimator Based on Singular Value Decomposition [PDF]
The Egyptian Statistical Journal, 2023 This paper aims to introduce a modification of the ridge estimator based on the singular value decomposition (SVD) technique of the design matrix (X ) to combat multicollinearity in the binary logistic model.
Monira Hussein, Mostafa Abd el-Rahman
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Most Likely Maximum Entropy for Population Analysis with Region-Censored Data
Entropy, 2015 The paper proposes a new non-parametric density estimator from region-censored observations with application in the context of population studies, where standard maximum likelihood is affected by over-fitting and non-uniqueness problems.
Youssef Bennani +2 more
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On the maximum likelihood estimator in the generalized beta regression model [PDF]
Opuscula Mathematica, 2012 The subject of this article is to present the beta - regression model, where we assume that one parameter in the model is described as a combination of algebraically independent continuous functions.
Jerzy P. Rydlewski, Dominik Mielczarek
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Semi-Nonparametric Maximum Likelihood Estimation [PDF]
Econometrica, 1987 The density of Hermite forms: \[ h(u)=P^ 2_ k(u-\tau)\Phi^ 2(u| \tau,diag(\gamma)) \] where \(P_ k\) is a polynomial of degree K and \(\Phi\) is the density function of the multivariate normal distribution is shown to be capable of approximating any density arbitrarily closely subject to minimal qualifications relating to compactness, denseness ...
Gallant, A Ronald, Nychka, Douglas W
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Consistency and Asymptotic Normality of the Maximum Likelihood Estimator in
IEEE Access, 2022 The Gamma distribution based generalized linear model ( $Ga$ GLM) is a kind of statistical model feasible for the positive value of a non-stationary stochastic system, in which the location and the scale are regressed by the corresponding explanatory ...
Benchao Wang, Pan Qin, Hong Gu
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A New Maximum Likelihood Estimator Formulated in Pole-Residue Modal Model
Applied Sciences, 2019 Recently, a lot of efforts have been devoted to developing more precise Modal Parameter Estimation (MPE) techniques. This is explained by the necessity in civil, mechanical and aerospace engineering of obtaining accurate estimates for the modal ...
Sandro Amador +3 more
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Maximum likelihood estimation of Wiener models [PDF]
Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187), 2002 A Wiener model consists of a linear dynamic system followed by a static nonlinearity. The input and output are measured, but not the intermediate signal. We discuss the maximum likelihood estimate for Gaussian measurement and process noise, and the special cases when one of the noise sources is zero.
Hagenblad, Anna, Ljung, Lennart
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Efficiency of Kimball's Linearized Maximum Likelihood Estimators for the Two Parameter Weibull and Extreme Value Distributions [PDF]
The Egyptian Statistical Journal, 1985 Asymptotic efficiencies, of Kimball's linearized maximum likelihood estimator β ̂ for the scale parameter of the Type I extreme value distribution are evaluated for Type II censored samples.
M. Habib, A. Bargal
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Implicit Maximum Likelihood Estimation
CoRR, 2018 Implicit probabilistic models are models defined naturally in terms of a sampling procedure and often induces a likelihood function that cannot be expressed explicitly. We develop a simple method for estimating parameters in implicit models that does not require knowledge of the form of the likelihood function or any derived quantities, but can be ...
Ke Li 0011, Jitendra Malik
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Estimating Maximum Likelihood Phylogenies with PhyML [PDF]
, 2009 Our understanding of the origins, the functions and/or the structures of biological sequences strongly depends on our ability to decipher the mechanisms of molecular evolution. These complex processes can be described through the comparison of homologous sequences in a phylogenetic framework.
Guindon, Stéphane +3 more
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