Theory of Ridge Regression Estimation with Applications
Theory of Ridge Regression Estimation with Applications

Author: A. K. Md. Ehsanes Saleh

Publisher: John Wiley & Sons

Published: 2019-01-08

Total Pages: 404

ISBN-13: 1118644506

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A guide to the systematic analytical results for ridge, LASSO, preliminary test, and Stein-type estimators with applications Theory of Ridge Regression Estimation with Applications offers a comprehensive guide to the theory and methods of estimation. Ridge regression and LASSO are at the center of all penalty estimators in a range of standard models that are used in many applied statistical analyses. Written by noted experts in the field, the book contains a thorough introduction to penalty and shrinkage estimation and explores the role that ridge, LASSO, and logistic regression play in the computer intensive area of neural network and big data analysis. Designed to be accessible, the book presents detailed coverage of the basic terminology related to various models such as the location and simple linear models, normal and rank theory-based ridge, LASSO, preliminary test and Stein-type estimators. The authors also include problem sets to enhance learning. This book is a volume in the Wiley Series in Probability and Statistics series that provides essential and invaluable reading for all statisticians. This important resource: Offers theoretical coverage and computer-intensive applications of the procedures presented Contains solutions and alternate methods for prediction accuracy and selecting model procedures Presents the first book to focus on ridge regression and unifies past research with current methodology Uses R throughout the text and includes a companion website containing convenient data sets Written for graduate students, practitioners, and researchers in various fields of science, Theory of Ridge Regression Estimation with Applications is an authoritative guide to the theory and methodology of statistical estimation.

Probability, Statistics, And Decision Making In The Atmospheric Sciences
Probability, Statistics, And Decision Making In The Atmospheric Sciences

Author: Allan Murphy

Publisher: CRC Press

Published: 2019-07-11

Total Pages: 560

ISBN-13: 1000236323

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Methodology drawn from the fields of probability. statistics and decision making plays an increasingly important role in the atmosphericsciences. both in basic and applied research and in experimental and operational studies. Applications of such methodology can be found in almost every facet of the discipline. from the most theoretical and global (e.g., atmospheric predictability. global climate modeling) to the most practical and local (e.g., crop-weather modeling forecast evaluation). Almost every issue of the multitude of journals published by the atmospheric sciences community now contain some or more papers involving applications of concepts and/or methodology from the fields of probability and statistics. Despite the increasingly pervasive nature of such applications. very few book length treatments of probabilistic and statistical topics of particular interest to atmospheric scientists have appeared (especially inEnglish) since the publication of the pioneering works of Brooks andCarruthers (Handbook of Statistical Methods in Meteorology) in 1953 and Panofsky and Brier-(some Applications of)statistics to Meteor) in 1958. As a result. many relatively recent developments in probability and statistics are not well known to atmospheric scientists and recent work in active areas of meteorological research involving significant applications of probabilistic and statistical methods are not familiar to the meteorological community as a whole.

Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences
Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences

Author: Jacob Cohen

Publisher: Routledge

Published: 2013-06-17

Total Pages: 735

ISBN-13: 1134800940

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This classic text on multiple regression is noted for its nonmathematical, applied, and data-analytic approach. Readers profit from its verbal-conceptual exposition and frequent use of examples. The applied emphasis provides clear illustrations of the principles and provides worked examples of the types of applications that are possible. Researchers learn how to specify regression models that directly address their research questions. An overview of the fundamental ideas of multiple regression and a review of bivariate correlation and regression and other elementary statistical concepts provide a strong foundation for understanding the rest of the text. The third edition features an increased emphasis on graphics and the use of confidence intervals and effect size measures, and an accompanying website with data for most of the numerical examples along with the computer code for SPSS, SAS, and SYSTAT, at www.psypress.com/9780805822236 . Applied Multiple Regression serves as both a textbook for graduate students and as a reference tool for researchers in psychology, education, health sciences, communications, business, sociology, political science, anthropology, and economics. An introductory knowledge of statistics is required. Self-standing chapters minimize the need for researchers to refer to previous chapters.

Flexible Imputation of Missing Data, Second Edition
Flexible Imputation of Missing Data, Second Edition

Author: Stef van Buuren

Publisher: CRC Press

Published: 2018-07-17

Total Pages: 444

ISBN-13: 0429960352

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Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes, like deletion or mean imputation, only work under highly restrictive conditions, which are often not met in practice. Multiple imputation replaces each missing value by multiple plausible values. The variability between these replacements reflects our ignorance of the true (but missing) value. Each of the completed data set is then analyzed by standard methods, and the results are pooled to obtain unbiased estimates with correct confidence intervals. Multiple imputation is a general approach that also inspires novel solutions to old problems by reformulating the task at hand as a missing-data problem. This is the second edition of a popular book on multiple imputation, focused on explaining the application of methods through detailed worked examples using the MICE package as developed by the author. This new edition incorporates the recent developments in this fast-moving field. This class-tested book avoids mathematical and technical details as much as possible: formulas are accompanied by verbal statements that explain the formula in accessible terms. The book sharpens the reader’s intuition on how to think about missing data, and provides all the tools needed to execute a well-grounded quantitative analysis in the presence of missing data.

Introduction to Small Area Estimation Techniques
Introduction to Small Area Estimation Techniques

Author: Asian Development Bank

Publisher: Asian Development Bank

Published: 2020-05-01

Total Pages: 152

ISBN-13: 9292622234

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This guide to small area estimation aims to help users compile more reliable granular or disaggregated data in cost-effective ways. It explains small area estimation techniques with examples of how the easily accessible R analytical platform can be used to implement them, particularly to estimate indicators on poverty, employment, and health outcomes. The guide is intended for staff of national statistics offices and for other development practitioners. It aims to help them to develop and implement targeted socioeconomic policies to ensure that the vulnerable segments of societies are not left behind, and to monitor progress toward the Sustainable Development Goals.

Applied Econometrics with R
Applied Econometrics with R

Author: Christian Kleiber

Publisher: Springer Science & Business Media

Published: 2008-12-10

Total Pages: 229

ISBN-13: 0387773185

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R is a language and environment for data analysis and graphics. It may be considered an implementation of S, an award-winning language initially - veloped at Bell Laboratories since the late 1970s. The R project was initiated by Robert Gentleman and Ross Ihaka at the University of Auckland, New Zealand, in the early 1990s, and has been developed by an international team since mid-1997. Historically, econometricians have favored other computing environments, some of which have fallen by the wayside, and also a variety of packages with canned routines. We believe that R has great potential in econometrics, both for research and for teaching. There are at least three reasons for this: (1) R is mostly platform independent and runs on Microsoft Windows, the Mac family of operating systems, and various ?avors of Unix/Linux, and also on some more exotic platforms. (2) R is free software that can be downloaded and installed at no cost from a family of mirror sites around the globe, the Comprehensive R Archive Network (CRAN); hence students can easily install it on their own machines. (3) R is open-source software, so that the full source code is available and can be inspected to understand what it really does, learn from it, and modify and extend it. We also like to think that platform independence and the open-source philosophy make R an ideal environment for reproducible econometric research.

Multi-frequency and multi-GNSS PPP phase bias estimation and ambiguity resolution
Multi-frequency and multi-GNSS PPP phase bias estimation and ambiguity resolution

Author: Xiao, Guorui

Publisher: KIT Scientific Publishing

Published: 2022-11-09

Total Pages: 154

ISBN-13: 3731510553

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Multi-frequency and multi-GNSS measurements from modernized satellites are properly integrated for PPP with ambiguity resolution to achieve the state-of-the-art fast and accurate positioning, which provides an important contribution to GNSS precise positioning and applications. The multi-frequency and multi-GNSS PPP phase bias estimation and ambiguity resolution, which is accomplished by a unified model based on the uncombined PPP, are thoroughly evaluated with special focus on Galileo and BDS.