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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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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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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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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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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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Econometric Modelling with Time Series

This book provides a general framework for specifying, estimating and testing time series econometric models. Special emphasis is given to;

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Econometric Modelling with Time Series

This book provides a general framework for specifying, estimating and testing time series econometric models. Special emphasis is given to;

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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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Analysis of Microdata

The book provides a simple, intuitive introduction to regression models for qualitative and discrete dependent variables, to sample;

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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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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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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

intricate models is usually based on the method of Maximum Likelihood, which is a well-established branch of mathematical statistics. Its use;

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Algebraic Geometry and Statistical Learning Theory

Sure to be influential, this book lays the foundations for the use of algebraic geometry in statistical learning theory. Many widely used;

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Fundamentals Of Item Response Theory

, test equating, and computerized-adaptive testing. The book also includes a thorough discussion of alternative procedures for estimating IRT;

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Statistical Theory and Inference

This text is for a one semester graduate course in statistical theory and covers minimal and complete sufficient statistics, maximum;

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Likelihood Free Methods for Cognitive Science

specification of a likelihood function. As a result, ABC can be used to estimate posterior distributions of parameters for simulation-based models;

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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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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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Data Analysis

Statistics lectures have been a source of much bewilderment and frustration for generations of students. This book attempts to remedy the;

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Meta-analysis of Binary Data Using Profile Likelihood

and extend it to cope with unobserved heterogeneity. They describe elements of log-linear modeling, ways for finding the profile maximum;

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Meta-analysis of Binary Data Using Profile Likelihood

and extend it to cope with unobserved heterogeneity. They describe elements of log-linear modeling, ways for finding the profile maximum;

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Introductory Statistical Inference with the Likelihood Function

necessary to understand and evaluate methods for analyzing complex data sets. The likelihood function is used for pure likelihood inference;

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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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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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Environmental Data Analysis

Environmental Data Analysis is an introductory statistics textbook for environmental science. It covers descriptive, inferential and;

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