{"product_id":"distributions-for-modeling-location-scale-and-shape-using-gamlss-in-r-paperback","title":"Distributions for Modeling Location, Scale, and Shape: Using Gamlss in R - 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\u003eRobert A. Rigby\u003c\/b\u003e (Author), \u003cb\u003eMikis D. Stasinopoulos\u003c\/b\u003e (Author), \u003cb\u003eGillian Z. Heller\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eThis is a book about statistical distributions, their properties, and their application to modelling the dependence of the location, scale, and shape of the distribution of a response variable on explanatory variables. It will be especially useful to applied statisticians and data scientists in a wide range of application areas, and also to those interested in the theoretical properties of distributions. This book follows the earlier book 'Flexible Regression and Smoothing: Using GAMLSS in R', [Stasinopoulos et al., 2017], which focused on the GAMLSS model and software. GAMLSS (the Generalized Additive Model for Location, Scale, and Shape, [Rigby and Stasinopoulos, 2005]), is a regression framework in which the response variable can have any parametric distribution and \u003ci\u003eall \u003c\/i\u003ethe distribution parameters can be modelled as linear or smooth functions of explanatory variables. The current book focuses on distributions and their application.\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eKey features: \u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cul\u003e \u003cp\u003e\u003c\/p\u003e\n\u003cp\u003e\u003c\/p\u003e \u003cli\u003eDescribes over 100 distributions, (implemented in the GAMLSS packages in R), including continuous, discrete and mixed distributions.\u003c\/li\u003e \u003cp\u003e\u003c\/p\u003e \u003c\/ul\u003e\u003cp\u003e\u003c\/p\u003e\u003cul\u003e \u003cp\u003e\u003c\/p\u003e\n\u003cp\u003e\u003c\/p\u003e \u003cli\u003eComprehensive summary tables of the properties of the distributions.\u003c\/li\u003e \u003cp\u003e\u003c\/p\u003e \u003c\/ul\u003e\u003cp\u003e\u003c\/p\u003e\u003cul\u003e \u003cp\u003e\u003c\/p\u003e\n\u003cp\u003e\u003c\/p\u003e \u003cli\u003eDiscusses properties of distributions, including skewness, kurtosis, robustness and an important classification of tail heaviness.\u003c\/li\u003e \u003cp\u003e\u003c\/p\u003e \u003c\/ul\u003e\u003cp\u003e\u003c\/p\u003e\u003cul\u003e \u003cp\u003e\u003c\/p\u003e\n\u003cp\u003e\u003c\/p\u003e \u003cli\u003eIncludes mixed distributions which are continuous distributions with additional specific values with point probabilities.\u003c\/li\u003e \u003cp\u003e\u003c\/p\u003e \u003c\/ul\u003e\u003cp\u003e\u003c\/p\u003e\u003cul\u003e \u003cp\u003e\u003c\/p\u003e\n\u003cp\u003e\u003c\/p\u003e \u003cli\u003eIncludes many real data examples, with R code integrated in the text for ease of understanding and replication.\u003c\/li\u003e \u003cp\u003e\u003c\/p\u003e \u003c\/ul\u003e\u003cp\u003e\u003c\/p\u003e\u003cul\u003e \u003cp\u003e\u003c\/p\u003e\n\u003cp\u003e\u003c\/p\u003e \u003cli\u003eSupplemented by the gamlss website.\u003c\/li\u003e \u003cp\u003e\u003c\/p\u003e \u003c\/ul\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eThis book will be useful for applied statisticians and data scientists in selecting a distribution for a univariate response variable and modelling its dependence on explanatory variables, and to those interested in the properties of distributions.\u003c\/p\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eRobert Rigby\u003c\/strong\u003e was researching in Statistics at London Metropolitan University for over 30 years specializing in distributions and advanced regression and smoothing models (for supervised learning). He is one of the two original developers of GAMLSS models. He is currently a freelance consultant.\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eMikis Stasinopoulos\u003c\/strong\u003e is a statistician. He has a considerable experience in applied statistics and he is one of the two creators of GAMLSS. He worked as the director of STORM, the statistics and mathematics research centre of London Metropolitan University and now he is working as an independent statistical consultant.\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eGillian Heller\u003c\/strong\u003e is Professor of Statistics at Macquarie University, Sydney. Her research interests are mainly in flexible regression models for heavy-tailed count data, with applications in biostatistics and insurance.\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eFernanda De Bastiani \u003c\/strong\u003eis a permanent lecturer in the Statistics Department at Universidade Federal de Pernambuco, Brazil. Her research interests are mainly in flexible regression models, spatial data analysis and influential diagnostics in regression models.\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 588\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 1.3 x 9.9 x 7 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e June 30, 2021\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":52705132511539,"sku":"9781032089423","price":149.54,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0300\/5595\/6612\/files\/V0FuTGtkUnFTb2FwbUVTd0JyL2JzUT09.webp?v=1763373358","url":"https:\/\/www.vysn.com\/en-ca\/products\/distributions-for-modeling-location-scale-and-shape-using-gamlss-in-r-paperback","provider":"VYSN","version":"1.0","type":"link"}