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An Improvement in Maximum Likelihood Estimation of the Gompertz Distribution Parameters
In this study, we will look at estimating the parameters of the Gompertz distribution. We know that the maximum likelihood technique is the most...
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On the Maximum Likelihood Estimation of Population and Domain Means
Estimating of population and domain means based on model-design approaches is considered in this paper. Population elements randomly belong to...
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A weighted average limited information maximum likelihood estimator
In this article, a Stein-type weighted limited information maximum likelihood (LIML) estimator is proposed. It is based on a weighted average of the...
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The Strong Consistency of Quasi-Maximum Likelihood Estimators for p-order Random Coefficient Autoregressive (RCA) Models
In this paper, we investigate the strong consistency of the quasi-maximum likelihood estimators derived through the Kalman filter for stationary...
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A constrained maximum likelihood estimation for skew normal mixtures
For a finite mixture of skew normal distributions, the maximum likelihood estimator is not well-defined because of the unboundedness of the...
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The modified maximum likelihood estimators for the parameters of the regression model under bivariate median ranked set sampling
We derived the modified maximum likelihood (MML) regression type estimators using bivariate median ranked set sampling (MRSS) and conducted an...
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Quasi-maximum likelihood estimation and penalized estimation under non-standard conditions
The purpose of this article is to develop a general parametric estimation theory that allows the derivation of the limit distribution of estimators...
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Nonparametric maximum likelihood estimation of the distribution function using ranked-set sampling
Kvam and Samaniego (J Am Stat Assoc 89: 526–537, 1994) derived an estimator that they billed as the nonparametric maximum likelihood estimator (MLE)...
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Maximum Likelihood Estimation Under Finite Mixture Models
Chapter 3 centers our attention on finite mixture models. Within this framework, we establish that the consistent results achieved with the maximum...
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Maximum Likelihood With a Time Varying Parameter
We consider the problem of tracking an unknown time varying parameter that characterizes the probabilistic evolution of a sequence of independent...
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Advances in Maximum Likelihood Estimation of Fixed-Effects Binary Panel Data Models
We review recent fixed-effects approaches to the formulation and estimation of models for binary panel data, measured at T time occasions. We offer a...
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Maximum Likelihood Estimation in Single Server Queues
In this paper, maximum likelihood estimation for the parameters in a single server queues are investigated. The queues are observed over a continuous...
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Improving the bias of a pseudo-maximum likelihood estimate of the extreme value index by k-records
The paper focusses on the estimation of the extreme value index in terms of k -records based on a maximum likelihood approach, which is suggested...
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Bayesian estimation versus maximum likelihood estimation in the Weibull-power law process
The Bayesian approach is applied to estimation of the Weibull-power law process (WPLP) parameters as an alternative to the maximum likelihood (ML)...
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Longitudinal mediation analysis through generalised linear mixed models: a comparison of maximum-likelihood and Bayesian estimation
The main goal of mediation analysis is to estimate the indirect effect of an exposure on a response variable conveyed by an intermediate variable...
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Simulation Study of Estimators of the Gamma Rate Parameter Using MLE as a Baseline Estimator
Classical estimation methods of the rate parameter of the gamma distribution have shown to have quality issues. In this paper we propose three...
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Generalized simulated method-of-moments estimators for multivariate copulas
This paper introduces a general semi-parametric method for estimating a vector of parameters in multivariate copula models. The proposed approach...
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Comparing Maximum Likelihood to Markov Chain Monte Carlo Estimation of the Multivariate Social Relations Model
The social relations model (SRM) is a linear random-effects model applied to dyadic data within social networks (i.e., round-robin data). Such data...
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Maximum Likelihood Estimation of Parameters of a Random Variable Using Monte Carlo Methods
In a parametric estimation framework, this paper proposes different properties for the maximum likelihood estimators of unknown parameters of a given...
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A note on maximum likelihood estimation for mixture models
Practitioners as well as some statistics students often blindly use standard software or algorithms to get maximum likelihood estimator (MLE) without...
