Asymptotics for Random Effects Models with Serial Correlation PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Asymptotics for Random Effects Models with Serial Correlation PDF full book. Access full book title Asymptotics for Random Effects Models with Serial Correlation by Jimmy Skoglund. Download full books in PDF and EPUB format.
Author: Jimmy Skoglund
Publisher:
ISBN:
Category :
Languages : en
Pages :
Get Book Here
Book Description
This paper considers the large sample behavior of the maximum likelihood estimator of random effects models. Consistent estimation and asymptotic normality as N and/or T grows large is established for a comprehensive specification which allows for serial correlation in the form of AR(1) for the idiosyncratic or time-specific error component. The consistency and asymptotic normality properties of all commonly used random effects models are obtained as special cases of the comprehensive model. When N or T >infty only a subset of the parameters are consistent and asymptotic normality is established for the consistent subsets.
Author: Jimmy Skoglund
Publisher:
ISBN:
Category :
Languages : en
Pages :
Get Book Here
Book Description
This paper considers the large sample behavior of the maximum likelihood estimator of random effects models. Consistent estimation and asymptotic normality as N and/or T grows large is established for a comprehensive specification which allows for serial correlation in the form of AR(1) for the idiosyncratic or time-specific error component. The consistency and asymptotic normality properties of all commonly used random effects models are obtained as special cases of the comprehensive model. When N or T >infty only a subset of the parameters are consistent and asymptotic normality is established for the consistent subsets.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :
Get Book Here
Book Description
The Stockholm School of Economics (SSE) Library presents the full text of the February 2001 paper entitled "Asymptotic Properties of the Maximum Likelihood Estimator of Random Effects Models with Serial Correlation," written by Jimmy Skoglund and Sune Karlsson. The text is available in PDF format and the paper is number 432 in the SEE/EFI Working Papers in Economics and Finance series. This paper discusses the large sample behavior of the maximum likelihood estimator of random effects models with serial correlation in the form of AR for the time-specific error component.
Author: Jiming Jiang
Publisher: CRC Press
ISBN: 1498700462
Category : Mathematics
Languages : en
Pages : 252
Get Book Here
Book Description
Large sample techniques are fundamental to all fields of statistics. Mixed effects models, including linear mixed models, generalized linear mixed models, non-linear mixed effects models, and non-parametric mixed effects models are complex models, yet, these models are extensively used in practice. This monograph provides a comprehensive account of asymptotic analysis of mixed effects models. The monograph is suitable for researchers and graduate students who wish to learn about asymptotic tools and research problems in mixed effects models. It may also be used as a reference book for a graduate-level course on mixed effects models, or asymptotic analysis.
Author: Sungwook Lee
Publisher:
ISBN:
Category : Biometry
Languages : en
Pages : 236
Get Book Here
Book Description
In this paper, we present a semiparametric regression model with random effects. Mixed models with fixed effects and random subject effects are popular in longitudinal studies where observations within each subject have a serial correlation and each subject has random variation. Recently, Moyeed and Diggle (1994) studied an additive model for longitudinal data with parametric and nonparametric terms without explicit random subject effects. A new method based on the partial linear model is presented, with explicit random effects. In this study, we will present theoretical asymptotic properties of the estimators of the parametric and nonparametric parts for balanced designs. Simulation results along with an analysis of real data are also considered for balanced and unbalanced design. Numerical results suggest that the new method performs better with unbalanced designs.
Author: Geert Verbeke
Publisher: Springer Science & Business Media
ISBN: 146122294X
Category : Medical
Languages : en
Pages : 319
Get Book Here
Book Description
A comprehensive treatment of linear mixed models, focusing on examples from designed experiments and longitudinal studies. Aimed at applied statisticians and biomedical researchers in industry, public health organisations, contract research organisations, and academia, this book is explanatory rather than mathematical rigorous. Although most analyses were done with the MIXED procedure of the SAS software package, and many of its features are clearly elucidated, considerable effort was put into presenting the data analyses in a software-independent fashion.
Author: Mahdi Alkhamisi
Publisher:
ISBN:
Category :
Languages : en
Pages : 240
Get Book Here
Book Description
Author: Alice Guionnet
Publisher: American Mathematical Soc.
ISBN: 1470450275
Category : Green's functions
Languages : en
Pages : 143
Get Book Here
Book Description
Probability theory is based on the notion of independence. The celebrated law of large numbers and the central limit theorem describe the asymptotics of the sum of independent variables. However, there are many models of strongly correlated random variables: for instance, the eigenvalues of random matrices or the tiles in random tilings. Classical tools of probability theory are useless to study such models. These lecture notes describe a general strategy to study the fluctuations of strongly interacting random variables. This strategy is based on the asymptotic analysis of Dyson-Schwinger (or loop) equations: the author will show how these equations are derived, how to obtain the concentration of measure estimates required to study these equations asymptotically, and how to deduce from this analysis the global fluctuations of the model. The author will apply this strategy in different settings: eigenvalues of random matrices, matrix models with one or several cuts, random tilings, and several matrices models.
Author: Jiming Jiang
Publisher:
ISBN: 9781315119281
Category : MATHEMATICS
Languages : en
Pages :
Get Book Here
Book Description
Author: Lang Wu
Publisher: CRC Press
ISBN: 9781420074086
Category : Mathematics
Languages : en
Pages : 431
Get Book Here
Book Description
Although standard mixed effects models are useful in a range of studies, other approaches must often be used in correlation with them when studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate approaches to address dropouts, missing data, measurement errors, censoring, and outliers. For each class of mixed effects model, the author reviews the corresponding class of regression model for cross-sectional data. An overview of general models and methods, along with motivating examples After presenting real data examples and outlining general approaches to the analysis of longitudinal/clustered data and incomplete data, the book introduces linear mixed effects (LME) models, generalized linear mixed models (GLMMs), nonlinear mixed effects (NLME) models, and semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values, measurement errors, censoring, and outliers. Self-contained coverage of specific topics Subsequent chapters delve more deeply into missing data problems, covariate measurement errors, and censored responses in mixed effects models. Focusing on incomplete data, the book also covers survival and frailty models, joint models of survival and longitudinal data, robust methods for mixed effects models, marginal generalized estimating equation (GEE) models for longitudinal or clustered data, and Bayesian methods for mixed effects models. Background material In the appendix, the author provides background information, such as likelihood theory, the Gibbs sampler, rejection and importance sampling methods, numerical integration methods, optimization methods, bootstrap, and matrix algebra. Failure to properly address missing data, measurement errors, and other issues in statistical analyses can lead to severely biased or misleading results. This book explores the biases that arise when naïve methods are used and shows which approaches should be used to achieve accurate results in longitudinal data analysis.
Author: Yves Croissant
Publisher: John Wiley & Sons
ISBN: 1118949188
Category : Mathematics
Languages : en
Pages : 328
Get Book Here
Book Description
Panel Data Econometrics with R provides a tutorial for using R in the field of panel data econometrics. Illustrated throughout with examples in econometrics, political science, agriculture and epidemiology, this book presents classic methodology and applications as well as more advanced topics and recent developments in this field including error component models, spatial panels and dynamic models. They have developed the software programming in R and host replicable material on the book’s accompanying website.
