A Model Selection Approach To Partially Linear Regression

DOWNLOAD

Download A Model Selection Approach To Partially Linear Regression PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get A Model Selection Approach To Partially Linear Regression book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page

A Model Selection Approach To Partially Linear Regression

DOWNLOAD
Author : Florentina Bunea
language : en
Publisher:
Release Date : 2000

A Model Selection Approach To Partially Linear Regression written by Florentina Bunea and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Regression analysis categories.

Partially Linear Models

DOWNLOAD
Author : Wolfgang Härdle
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Partially Linear Models written by Wolfgang Härdle and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.

In the last ten years, there has been increasing interest and activity in the general area of partially linear regression smoothing in statistics. Many methods and techniques have been proposed and studied. This monograph hopes to bring an up-to-date presentation of the state of the art of partially linear regression techniques. The emphasis is on methodologies rather than on the theory, with a particular focus on applications of partially linear regression techniques to various statistical problems. These problems include least squares regression, asymptotically efficient estimation, bootstrap resampling, censored data analysis, linear measurement error models, nonlinear measurement models, nonlinear and nonparametric time series models.

Recent Advances In Statistical Models

DOWNLOAD
Author : Wenqian Qiao
language : en
Publisher:
Release Date : 2012

Recent Advances In Statistical Models written by Wenqian Qiao and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Statistics categories.

This dissertation consists of three chapters. It develops new methodologies to address two specific problems of recent statistical research: * How to incorporate hierarchical structure in high dimensional regression model selection. * How to achieve semi-parametric efficiency in the presence of missing data. For the first problem, we provide a new approach to explicitly incorporate a given hierarchical structure among the predictors into high dimensional regression model selection. The proposed estimation approach has a hierarchical grouping property so that a pair of variables that are "close" in the hierarchy will be more likely grouped in the estimated model than those that are "far away". We also prove that the proposed method can consistently select the true model. These properties are demonstrated numerically in simulation and a real data analysis on peripheral-blood mononuclear cell (PBMC) study. For the second problem, two frameworks are considered: generalized partially linear model (GPLM) and causal inference of observational study. Specifically, under the GPLM framework, we consider a broad range of missing patterns which subsume most publications on the same topic. We use the concept of least favorable curve and extend the generalized profile likelihood approach [Severini and Wong (1992)] to estimate the parametric component of the model, and prove that the proposed estimator is consistent and semi-parametrically efficient. Also, under the causal inference framework, we propose to estimate the mean treatment effect with non-randomized treatment exposures in the presence of missing data. An appealing aspect of this development is that we incorporate the post-baseline covariates which are often excluded from causal effect inference due to their inherent confounding effect with treatment. We derive the semiparametric efficiency bound for regular asymptotically linear (RAL) estimators and propose an estimator which achieves this bound. Moreover, we prove that the proposed estimator is robust against four types of model mis-specifications. The performance of the proposed approaches are illustrated numerically through simulations and real data analysis on group testing dataset from Nebraska Infertility Prevention Project and burden of illness dataset from Duke University Medical Center.

Regression And Time Series Model Selection

DOWNLOAD
Author : Allan D. R. McQuarrie
language : en
Publisher: World Scientific
Release Date : 1998

Regression And Time Series Model Selection written by Allan D. R. McQuarrie and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Mathematics categories.

This important book describes procedures for selecting a model from a large set of competing statistical models. It includes model selection techniques for univariate and multivariate regression models, univariate and multivariate autoregressive models, nonparametric (including wavelets) and semiparametric regression models, and quasi-likelihood and robust regression models. Information-based model selection criteria are discussed, and small sample and asymptotic properties are presented. The book also provides examples and large scale simulation studies comparing the performances of information-based model selection criteria, bootstrapping, and cross-validation selection methods over a wide range of models.

Linear Regression Analysis

DOWNLOAD
Author : Xin Yan
language : en
Publisher: World Scientific
Release Date : 2009

Linear Regression Analysis written by Xin Yan and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Mathematics categories.

This volume presents in detail the fundamental theories of linear regression analysis and diagnosis, as well as the relevant statistical computing techniques so that readers are able to actually model the data using the methods and techniques described in the book. It covers the fundamental theories in linear regression analysis and is extremely useful for future research in this area. The examples of regression analysis using the Statistical Application System (SAS) are also included. This book is suitable for graduate students who are either majoring in statistics/biostatistics or using linear regression analysis substantially in their subject fields.

A Consistent Test For Linearity In Partially Linear Regression Models

DOWNLOAD
Author : University of Guelph. Department of Economics
language : en
Publisher:
Release Date : 1994

A Consistent Test For Linearity In Partially Linear Regression Models written by University of Guelph. Department of Economics and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with categories.

Linear Models And Regression With R An Integrated Approach

DOWNLOAD
Author : Debasis Sengupta
language : en
Publisher: World Scientific
Release Date : 2019-07-30

Linear Models And Regression With R An Integrated Approach written by Debasis Sengupta and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-30 with Mathematics categories.

Starting with the basic linear model where the design and covariance matrices are of full rank, this book demonstrates how the same statistical ideas can be used to explore the more general linear model with rank-deficient design and/or covariance matrices. The unified treatment presented here provides a clearer understanding of the general linear model from a statistical perspective, thus avoiding the complex matrix-algebraic arguments that are often used in the rank-deficient case. Elegant geometric arguments are used as needed.The book has a very broad coverage, from illustrative practical examples in Regression and Analysis of Variance alongside their implementation using R, to providing comprehensive theory of the general linear model with 181 worked-out examples, 227 exercises with solutions, 152 exercises without solutions (so that they may be used as assignments in a course), and 320 up-to-date references.This completely updated and new edition of Linear Models: An Integrated Approach includes the following features:

Linear Regression Analysis With Jmp And R

DOWNLOAD
Author : Rachel T. Silvestrini
language : en
Publisher: Quality Press
Release Date : 2018-04-26

Linear Regression Analysis With Jmp And R written by Rachel T. Silvestrini and has been published by Quality Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-26 with Education categories.

This comprehensive but low-cost textbook is intended for use in an undergraduate level regression course, as well as for use by practitioners. The authors have included some statistical details throughout the book but focus on interpreting results for real applications of regression analysis. Chapters are devoted to data collection and cleaning; data visualization; model fitting and inference; model prediction and inference; model diagnostics; remedial measures; model selection techniques; model validation; and a case study demonstrating the techniques outlined throughout the book. The examples throughout each chapter are illustrated using the software packages R and JMP. At the end of each chapter, there is a tutorial section demonstrating the use of both R and JMP. The R tutorial contains source code and the JMP tutorial contains a step by step guide. Each chapter also includes exercises for further study and learning.

Linear Regression

DOWNLOAD
Author : David J. Olive
language : en
Publisher: Springer
Release Date : 2017-04-18

Linear Regression written by David J. Olive and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-18 with Mathematics categories.

This text covers both multiple linear regression and some experimental design models. The text uses the response plot to visualize the model and to detect outliers, does not assume that the error distribution has a known parametric distribution, develops prediction intervals that work when the error distribution is unknown, suggests bootstrap hypothesis tests that may be useful for inference after variable selection, and develops prediction regions and large sample theory for the multivariate linear regression model that has m response variables. A relationship between multivariate prediction regions and confidence regions provides a simple way to bootstrap confidence regions. These confidence regions often provide a practical method for testing hypotheses. There is also a chapter on generalized linear models and generalized additive models. There are many R functions to produce response and residual plots, to simulate prediction intervals and hypothesis tests, to detect outliers, and to choose response transformations for multiple linear regression or experimental design models. This text is for graduates and undergraduates with a strong mathematical background. The prerequisites for this text are linear algebra and a calculus based course in statistics.

Partially Linear Model Selection

DOWNLOAD
Author : Samuel Müller
language : en
Publisher:
Release Date : 2005

Partially Linear Model Selection written by Samuel Müller and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with categories.