The Use of Generalized Inverses in Restricted Maximum Likelihood PDF Download

Author: Henk Don
Publisher:
ISBN:
Category : Regression analysis
Languages : en
Pages : 26

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Author: Frederick van Der Ploeg
Publisher: Academic Press
ISBN: 148327036X
Category : Business & Economics
Languages : en
Pages : 649

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Advanced Lectures in Quantitative Economics summarizes some of the efforts of a second-phase program for first-rate candidates with a Master's degree in economics who wish to continue with a doctoral degree in quantitative economics. This book is organized into three main topics—macroeconomics, microeconomics, and econometrics. This text specifically discusses the Neo-Keynesian macroeconomics in an open economy, international coordination of monetary policies under alternative exchange-rate regimes, and prospects for global trade imbalances. The post-war developments in labor economics, introduction to overlapping generation models, and measurement of expectations and direct tests of the REH are also elaborated. This monograph likewise covers the dynamic econometric modeling of decisions under uncertainty and fundamental bordered matrix of linear estimation. This publication is a good reference for students and specialists interested in quantitative economics.

Author: Jayalakshmi Krishnakumar
Publisher: Springer Science & Business Media
ISBN: 3642456472
Category : Business & Economics
Languages : en
Pages : 371

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Economists can rarely perform controlled experiments to generate data. Existing information in the form of real-life observations simply has to be utilized in the best possible way. Given this, it is advantageous to make use of the increasing availability and accessibility of combinations of time-series and cross-sectional data in the estimation of economic models. But such data call for a new methodology of estimation and hence for the development of new econometric models. This book proposes one such new model which introduces error components in a system of simultaneous equations to take into account the temporal and cross-sectional heterogeneity of panel data. After a substantial survey of panel data models, the newly proposed model is presented in detail and indirect estimations, full information and limited information estimations, and estimations with and without the assumption of normal distribution errors. These estimation methods are then applied using a computer to estimate a model of residential electricity demand using data on American households. The results are analysed both from an economic and from a statistical point of view.

Author: László Mátyás
Publisher: Springer Science & Business Media
ISBN: 9400903758
Category : Business & Economics
Languages : en
Pages : 564

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The aim of this volume is to provide a general overview of the econometrics of panel data, both from a theoretical and from an applied viewpoint. Since the pioneering papers by Kuh (1959), Mundlak (1961), Hoch (1962), and Balestra and Nerlove (1966), the pooling of cross section and time series data has become an increasingly popular way of quantifying economic relationships. Each series provides information lacking in the other, so a combination of both leads to more accurate and reliable results than would be achievable by one type of series alone. Over the last 30 years much work has been done: investigation of the properties of the applied estimators and test statistics, analysis of dynamic models and the effects of eventual measurement errors, etc. These are just some of the problems addressed by this work. In addition, some specific diffi culties associated with the use of panel data, such as attrition, heterogeneity, selectivity bias, pseudo panels etc., have also been explored. The first objective of this book, which takes up Parts I and II, is to give as complete and up-to-date a presentation of these theoretical developments as possible. Part I is concerned with classical linear models and their extensions; Part II deals with nonlinear models and related issues: logit and probit models, latent variable models, incomplete panels and selectivity bias, and point processes.

Author: C. Folmer
Publisher: Elsevier
ISBN: 1483290530
Category : Business & Economics
Languages : en
Pages : 360

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The reform of the Common Agricultural Policy (CAP) which is now being implemented, reduces the support for a selected number of agricultural products. This book uses welfare theory and applied general equilibrium analysis to assess the medium to long term consequences of this reform, if the new policies remain in place until the beginning of the next century. It analyses the implications of two alternative scenarios: a) a further trade liberalisation covering all commodities; and b) increased protectionism with high prices, constraints on production and export subsidies (financed by the farmers themselves). The study also investigates the implications of financial renationalisation, whereby the European Union member-states would cover the costs of their own support measures.

Author:
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 400

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Author: Shayle R. Searle
Publisher: John Wiley & Sons
ISBN: 0470317698
Category : Mathematics
Languages : en
Pages : 537

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WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. ". . .Variance Components is an excellent book. It is organized and well written, and provides many references to a variety of topics. I recommend it to anyone with interest in linear models." —Journal of the American Statistical Association "This book provides a broad coverage of methods for estimating variance components which appeal to students and research workers . . . The authors make an outstanding contribution to teaching and research in the field of variance component estimation." —Mathematical Reviews "The authors have done an excellent job in collecting materials on a broad range of topics. Readers will indeed gain from using this book . . . I must say that the authors have done a commendable job in their scholarly presentation." —Technometrics This book focuses on summarizing the variability of statistical data known as the analysis of variance table. Penned in a readable style, it provides an up-to-date treatment of research in the area. The book begins with the history of analysis of variance and continues with discussions of balanced data, analysis of variance for unbalanced data, predictions of random variables, hierarchical models and Bayesian estimation, binary and discrete data, and the dispersion mean model.

Author: Eugene Demidenko
Publisher: John Wiley & Sons
ISBN: 1118592999
Category : Mathematics
Languages : en
Pages : 768

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Praise for the First Edition “This book will serve to greatly complement the growing number of texts dealing with mixed models, and I highly recommend including it in one’s personal library.” —Journal of the American Statistical Association Mixed modeling is a crucial area of statistics, enabling the analysis of clustered and longitudinal data. Mixed Models: Theory and Applications with R, Second Edition fills a gap in existing literature between mathematical and applied statistical books by presenting a powerful examination of mixed model theory and application with special attention given to the implementation in R. The new edition provides in-depth mathematical coverage of mixed models’ statistical properties and numerical algorithms, as well as nontraditional applications, such as regrowth curves, shapes, and images. The book features the latest topics in statistics including modeling of complex clustered or longitudinal data, modeling data with multiple sources of variation, modeling biological variety and heterogeneity, Healthy Akaike Information Criterion (HAIC), parameter multidimensionality, and statistics of image processing. Mixed Models: Theory and Applications with R, Second Edition features unique applications of mixed model methodology, as well as: Comprehensive theoretical discussions illustrated by examples and figures Over 300 exercises, end-of-section problems, updated data sets, and R subroutines Problems and extended projects requiring simulations in R intended to reinforce material Summaries of major results and general points of discussion at the end of each chapter Open problems in mixed modeling methodology, which can be used as the basis for research or PhD dissertations Ideal for graduate-level courses in mixed statistical modeling, the book is also an excellent reference for professionals in a range of fields, including cancer research, computer science, and engineering.

Author: Mikis D. Stasinopoulos
Publisher: Cambridge University Press
ISBN: 1009410059
Category : Mathematics
Languages : en
Pages : 308

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This text provides a state-of-the-art treatment of distributional regression, accompanied by real-world examples from diverse areas of application. Maximum likelihood, Bayesian and machine learning approaches are covered in-depth and contrasted, providing an integrated perspective on GAMLSS for researchers in statistics and other data-rich fields.

Author: Wilfrid Joseph Dixon
Publisher: Univ of California Press
ISBN: 9780520071131
Category : Mathematics
Languages : en
Pages : 784

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