{"product_id":"linear-models-and-regression-with-r-an-integrated-approach-paperback","title":"Linear Models and Regression with R: An Integrated Approach - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eSenGupta Debasis\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eStarting 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.\u003c\/p\u003e\u003cp\u003eThe 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.\u003c\/p\u003e\u003cp\u003eThis completely updated and new edition of \u003cem\u003eLinear Models: An Integrated Approach\u003c\/em\u003e includes the following features: \u003c\/p\u003e \u003cul\u003e \u003cli\u003eApplications with data sets, and their implementation in R, \u003c\/li\u003e \u003cli\u003eComprehensive coverage of regression diagnostics and model building, \u003c\/li\u003e \u003cli\u003eCoverage of other special topics such as collinearity, stochastic and inequality constraints, misspecified models, etc., \u003c\/li\u003e \u003cli\u003eUse of simple statistical ideas and interpretations to explain advanced concepts, and simpler proofs of many known results, \u003c\/li\u003e \u003cli\u003eDiscussion of models covering mixed-effects\/variance components, spatial, and time series data with partially unknown dispersion matrix, \u003c\/li\u003e \u003cli\u003eThorough treatment of the singular linear model, including the case of multivariate response, \u003c\/li\u003e \u003cli\u003eInsight into updates in the linear model, and their connection with diagnostics, design, variable selection, Kalman filter, etc., \u003c\/li\u003e \u003cli\u003eExtensive discussion of the foundations of linear inference, along with linear alternatives to least squares.\u003c\/li\u003e \u003c\/ul\u003e\u003ch3\u003eFront Jacket\u003c\/h3\u003e\u003cp\u003eStarting 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. \u003c\/p\u003e\u003cp\u003e 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. \u003c\/p\u003e\u003cp\u003e This completely updated and new edition of Linear Models: An Integrated Approach includes the following features: \u003c\/p\u003e\u003cp\u003e Applications with data sets, and their implementation in R, \u003c\/p\u003e\u003cp\u003e Comprehensive coverage of regression diagnostics and model building, \u003c\/p\u003e\u003cp\u003e Coverage of other special topics such as collinearity, stochastic and inequality constraints, misspecified models, etc., \u003c\/p\u003e\u003cp\u003e Use of simple statistical ideas and interpretations to explain advanced concepts, and simpler proofs of many known results, \u003c\/p\u003e\u003cp\u003e Discussion of models covering mixed-effects\/variance components, spatial, and time series data with partially unknown dispersion matrix, \u003c\/p\u003e\u003cp\u003e Thorough treatment of the singular linear model, including the case of multivariate response, \u003c\/p\u003e\u003cp\u003e Insight into updates in the linear model, and their connection with diagnostics, design, variable selection, Kalman filter, etc., \u003c\/p\u003e\u003cp\u003e Extensive discussion of the foundations of linear inference, along with linear alternatives to least squares.\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 772\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 1.54 x 9 x 6 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e August 10, 2019\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":53125770215731,"sku":"9789811229282","price":117.16,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0300\/5595\/6612\/files\/CJAzc78HA09789811229282.webp?v=1773260268","url":"https:\/\/www.vysn.com\/en-ca\/products\/linear-models-and-regression-with-r-an-integrated-approach-paperback","provider":"VYSN","version":"1.0","type":"link"}