نتایج جستجو برای: maximum likelihood estimator mle

تعداد نتایج: 382940  

2017
Lukun Zheng Jiancheng Jiang

*Correspondence: [email protected] 2Department of Mathematics and Statistics, UNC Charlotte, 9201 University City Blvd, 28223 Charlotte, USA Full list of author information is available at the end of the article Abstract The maximum likelihood estimator (MLE) of Gini-Simpson’s diversity index (GS) is widely used but suffers from large bias when the number of species is large or infinite. We prop...

Journal: :CoRR 2016
Weiping Zhu

Although there are a few works reported in the literature considering loss tomography in the general topology, there is few well established result since all of them rely either on simulations or on experiments that have many random factors affecting the outcome. To improve the situation, we address a number of issues in this paper that include a maximum likelihood estimator (MLE) for the gener...

2009
R. Dennis Cook Bing Li Francesca Chiaromonte FRANCESCA CHIAROMONTE

We propose a new parsimonious version of the classical multivariate normal linear model, yielding a maximum likelihood estimator (MLE) that is asymptotically less variable than the MLE based on the usual model. Our approach is based on the construction of a link between the mean function and the covariance matrix, using the minimal reducing subspace of the latter that accommodates the former. T...

2013
Joscha Diehl Peter K. Friz Hilmar Mai

We consider the estimation problem of an unknown drift parameter within classes of non-degenerate diffusion processes. The Maximum Likelihood Estimator (MLE) is analyzed with regard to its pathwise stability properties and robustness towards misspecification in volatility and even the very nature of noise. We construct a version of the estimator based on rough integrals (in the sense of T. Lyon...

1998
Gonzalo Seco-Granados Juan A. Fernández-Rubio

The problem of estimating the propagation-delay of a desired signal in the presence of interferences and multipath propagation is addressed. This paper presents the maximum likelihood (ML) propagation-delay estimator for a signal arriving at a sensor array. The novel characteristic herein is that the desired signal impinges on the array with a known steering vector. This fact allows to assume a...

Journal: :Communications in Statistics 2021

In cluster-specific studies, ordinary logistic regression and conditional for binary outcomes provide maximum likelihood estimator (MLE) (CMLE), respectively. this paper, we show that CMLE is approaching to MLE asymptotically when each individual data point replicated infinitely many times. Our theoretical derivation based on the observation a term appearing in average log-likelihood function c...

2008
Cheng-Der Fuh

Motivated by studying asymptotic properties of the maximum likelihood estimator (MLE) in stochastic volatility (SV) models, in this paper we investigate likelihood estimation in state space models. We first prove, under some regularity conditions, there is a consistent sequence of roots of the likelihood equation that is asymptotically normal with the inverse of the Fisher information as its va...

1994
Jian Huang

The maximum likelihood estimator (MLE) for the proportional hazards model with current status data is studied. It is shown that the MLE for the regression parameter is asymptotically normal with vn-convergence rate and achieves the information bound, even though the MLE for the baseline cumulative hazard function only converges at nI/3 rate. Estimation of the asymptotic variance matrix for the ...

Journal: :international journal of civil engineering 0
sh. afandizadeh iran university of science and technology s.a.h zahabi iran university of science and technology n. kalantari iran university of science and technology

logit models are one of the most important discrete choice models and they play an important role in describing decision makers’ choices among alternatives. in this paper the multi-nominal logit models has been used in mode choice modeling of isfahan. despite the availability of different mathematical computer programs there are not so many programs available for estimating discrete choice mode...

2007
Rebecca Fiebrink Chenwei Zhu

This lecture covers the basics of core concepts in probability and statistics to be used in the course. These include random variables, continuous and discrete distributions, joint and conditional distributions, the chain rule, marginalization, Bayes Rule, independence and conditional independence, and expectation. Probability models are discussed along with the concepts of independently and id...

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