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Maximum Likelihood Estimation and Inference

This book takes a fresh look at the popular and well-established method of maximum likelihood for statistical estimation and inference. It;

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Parametric Inference: An Introduction

on consistent asymptotically normal estimators obtained by method of moments, percentile and the method of maximum likelihood is also;

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Estimation, Inference and Specification Analysis

of likelihood-based methods of statistical estimation and interference. Professor White first explores the underlying motivation for maximum-likelihood;

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Mathematical Foundations of Infinite-Dimensional Statistical Models

In nonparametric and high-dimensional statistical models, the classical Gauss-Fisher-Le Cam theory of the optimality of maximum likelihood;

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Estimation, Inference and Specification Analysis

of likelihood-based methods of statistical estimation and interference. Professor White first explores the underlying motivation for maximum-likelihood;

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Maximum Likelihood Estimation for Sample Surveys

population and standard application of likelihood methods can lead to biased and inefficient estimates. Maximum Likelihood Estimation for Sample;

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Introductory Statistical Inference with the Likelihood Function

psychometricians. After a brief introduction, there are chapters on estimation, hypothesis testing, and maximum likelihood modeling. The book concludes;

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Maximum Likelihood Estimation with Stata, Fourth Edition

Maximum Likelihood Estimation with Stata, Fourth Edition is written for researchers in all disciplines who need to compute maximum;

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Econometric Modelling with Time Series

estimation, nonparametric estimation and estimation by simulation. An important advantage of adopting the principle of maximum likelihood as the;

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Econometric Modelling with Time Series

estimation, nonparametric estimation and estimation by simulation. An important advantage of adopting the principle of maximum likelihood as the;

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Antedependence Models for Longitudinal Data

methods. They then present formal likelihood-based procedures for normal antedependence models, including maximum likelihood and residual maximum;

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Statistical Inference

maximum-likelihood method of estimation, Neyman's shortest confidence interval, classical and Bayesian approach. The difference between;

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Spatial and Spatiotemporal Econometrics

This volume focuses on econometric models that confront estimation and inference issues occurring when sample data exhibit spatial or;

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Fundamental Statistical Inference

moment) estimation, and a variety of methods of point estimation besides maximum likelihood, including use of characteristic functions, and;

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Likelihood

This new and expanded edition of A. W. F. Edwards' classic volume on scientific inference presents his most important published articles on;

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Copula Modeling

copulas is that estimation and inference are based on standard maximum likelihood procedures. Thus, copulas can be estimated using desktop;

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Fundamentals Of Item Response Theory

parameters, such as maximum likelihood estimation, marginal maximum likelihood estimation, and Bayesian estimation in such a way that the reader does;

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Likelihood and Bayesian Inference

likelihood-based inference from a frequentist viewpoint, and exploring the properties of the maximum likelihood estimate, the score function, the;

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Likelihood & Bayesian Inference

likelihood-based inference from a frequentist viewpoint, and exploring the properties of the maximum likelihood estimate, the score function, the;

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Two Essays on Maximum Likelihood Estimation

maximum likelihood estimation of DSGE models. The first essay focuses on a monetary DSGE model of term structure, and the estimation of its;

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A Graduate Course on Statistical Inference

This textbook offers an accessible and comprehensive overview of statistical estimation and inference that reflects current trends;

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Essential Statistical Inference

likelihood, Bayesian, and permutation inference; an introduction to basic asymptotic distribution theory; and modern topics like M-estimation, the;

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Statistical Inference

: The estimation and hypothesis testing problems for both discrete and continuous models The robustness properties and the structural geometry;

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Statistical Inference

different ways of constructing an appropriate distance between the data and the model: the scope of study referred to by Minimum Distance Estimation;

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Mathematical Statistics

Presents a unified approach to parametric estimation, confidence intervals, hypothesis testing, and statistical modeling, which are;

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Bioinformatics and Phylogenetics

phylogenetic tree and network estimation, genome rearrangements, cancer phylogeny, species trees, divide-and-conquer strategies, and integer linear;

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Maximum Likelihood for Social Science

This volume provides a practical introduction to the method of maximum likelihood as used in social science research. Ward and Ahlquist;

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