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[null,"1.","Record Nr.",null,"UNINA9910830180503321"]
[null,null,"Autore",null,"Saleh A. K. Md. Ehsanes"]
[null,null,"Titolo",null,"Theory of ridge regression estimators with applications / / A. K. Md. Ehsanes Saleh, M. Arashi, B. M. Golam Kibria"]
[null,null,"Pubbl/distr/stampa",null,"Hoboken, New Jersey : , : Wiley, , 2019"]
[null,null,"ISBN",null,"1-118-64452-2"]
[{"$nulls":4},"1-118-64450-6"]
[{"$nulls":4},"1-118-64447-6"]
[null,null,"Edizione",null,"[1st edition]"]
[null,null,"Descrizione fisica",null,"1 online resource (299 pages)"]
[null,null,"Collana",null,"Wiley series in probability and statistics"]
[null,null,"Disciplina",null,"519.536"]
[null,null,"Soggetti",null,"Ridge regression (Statistics)"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Includes index."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Introduction to ridge regression -- Location and simple linear models -- ANOVA model -- Seemingly unrelated simple linear models -- Multiple linear regression models -- Ridge regression in theory and applications -- Partially linear regression models -- Logistic regression model -- Regression models with autoregressive errors -- Rank-based shrinkage estimation -- High dimensional ridge regression -- Applications : neural networks and big data."]
[null,null,null,"Sommario/riassunto","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.\u2028The 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 "]
[{"$nulls":4},"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."]