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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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Parametric Inference: An Introduction

variance unbiased estimator. There is a separate chapter on simultaneous estimation of several parameters. Large sample theory of estimation, based;

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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 by maximum likelihood, but other methods are also discussed, including quasi-maximum likelihood estimation, generalised method of moments;

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Econometric Modelling with Time Series

estimation by maximum likelihood, but other methods are also discussed, including quasi-maximum likelihood estimation, generalised method of moments;

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Regression Models

What techniques can social scientists use when an outcome variable for a sample (for example, y) is not representative of the population;

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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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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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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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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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Randomized Response and Indirect Questioning Techniques in Surveys

features is valid for selecting respondents in a general manner. The author examines different ways to treat maximum likelihood estimation; covers;

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Randomized Response and Indirect Questioning Techniques in Surveys

features is valid for selecting respondents in a general manner. The author examines different ways to treat maximum likelihood estimation; covers;

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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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Statistical Inference

Intended as a text for the postgraduate students of statistics, this well-written book gives a complete coverage of Estimation theory and;

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Separating Information Maximum Likelihood Method for High-Frequency Financial Data

This book presents a systematic explanation of the SIML (Separating Information Maximum Likelihood) method, a new approach to financial;

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Shrinkage Estimation for Mean and Covariance Matrices

This book provides a self-contained introduction to shrinkage estimation for matrix-variate normal distribution models. More specifically;

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Analysis of Microdata

selection models, and to event history models, all in the context of maximum likelihood estimation. It presents a wide range of commonly used models;

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Methods of Statistical Model Estimation

Methods of Statistical Model Estimation examines the most important and popular methods used to estimate parameters for statistical models;

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Methods of Statistical Model Estimation

Methods of Statistical Model Estimation examines the most important and popular methods used to estimate parameters for statistical models;

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Handbook Of Applied Econometrics And Statistical Inference

implementation of sample surveys, advances in the theory of Neyman's smooth test, and methods for pre-test and biased estimation. It includes discussions;

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Handbook Of Applied Econometrics And Statistical Inference

implementation of sample surveys, advances in the theory of Neyman's smooth test, and methods for pre-test and biased estimation. It includes discussions;

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Modeling and Estimation of Structural Damage

of probability theory and random processes Covers both theory and algorithms for implementing maximum likelihood and Bayesian estimation approaches;

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Mathematical Foundations of Infinite-Dimensional Statistical Models

maximum likelihood estimation. In a final chapter the theory of adaptive inference in nonparametric models is developed, including Lepski's method;

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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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Econometric Analysis Of Time Series

of maximum likelihood playing a key role in both estimation and testing. Exercises are included and the book is suitable as a general text for final;

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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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Econometric Applications of Maximum Likelihood Methods

many interesting ideas were not followed up because the calculations involved made this impracticable. The estimation and testing of these more;

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