LEADER 03701nam 2200481 450 001 9910830180503321 005 20190923044549.0 010 $a1-118-64452-2 010 $a1-118-64450-6 010 $a1-118-64447-6 035 $a(CKB)4330000000006680 035 $a(MiAaPQ)EBC5630671 035 $a(CaSebORM)9781118644614 035 $a(EXLCZ)994330000000006680 100 $a20190128d2019 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aTheory of ridge regression estimators with applications /$fA. K. Md. Ehsanes Saleh, M. Arashi, B. M. Golam Kibria 205 $a1st edition 210 1$aHoboken, New Jersey :$cWiley,$d2019. 215 $a1 online resource (299 pages) 225 1 $aWiley series in probability and statistics 300 $aIncludes index. 311 $a1-118-64461-1 320 $aIncludes bibliographical references and index. 327 $aIntroduction 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. 330 $aA 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. 606 $aRidge regression (Statistics) 615 0$aRidge regression (Statistics) 676 $a519.536 700 $aSaleh$b A. K. Md. Ehsanes$0150888 702 $aKibria$b B. M. G.$g(B. M. Golam),$f1963- 702 $aArashi$b M$g(Mohammad),$f1981- 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910830180503321 996 $aTheory of ridge regression estimators with applications$93934982 997 $aUNINA