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[null,"1.","Record Nr.",null,"UNINA9910701949903321"]
[null,null,"Autore",null,"Wilde Parke"]
[null,null,"Titolo",null,"Understanding the Food Stamp benefit formula [[electronic resource] ] : a tool for measuring the component effects / / Parke Wilde"]
[null,null,"Pubbl/distr/stampa",null,"[Washington, D.C.?] : , : U.S. Dept. of Agriculture, Economic Research Service, , [2001]"]
[null,null,"Descrizione fisica",null,"1 online resource (iii, 19 leaves)"]
[null,null,"Collana",null,"Food Assistance and Nutrition Research report ; ; no. 14"]
[null,null,"Soggetti",null,"Food relief - United States - Evaluation"]
[{"$nulls":4},"Food stamps - United States - Mathematical models"]
[{"$nulls":4},"Food stamps - United States - Computer simulation"]
[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","Title from title screen (viewed July 19, 2012)."]
[{"$nulls":4},"\"April 2001.\""]
[null,null,null,"Nota di bibliografia","Includes bibliographical references (page 14)."]
[null,"2.","Record Nr.",null,"UNINA9910300139903321"]
[null,null,"Autore",null,"Alvo Mayer"]
[null,null,"Titolo",null,"A Parametric Approach to Nonparametric Statistics / / by Mayer Alvo, Philip L. H. Yu"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018"]
[null,null,"ISBN",null,"3-319-94153-4"]
[null,null,"Edizione",null,"[1st ed. 2018.]"]
[null,null,"Descrizione fisica",null,"1 online resource (XIV, 279 p. 15 illus. in color.)"]
[null,null,"Collana",null,"Springer Series in the Data Sciences, , 2365-5682"]
[null,null,"Disciplina",null,"519.54"]
[null,null,"Soggetti",null,"Probabilities"]
[{"$nulls":4},"Statistics"]
[{"$nulls":4},"Probability Theory"]
[{"$nulls":4},"Statistical Theory and Methods"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"I. Introduction and Fundamentals -- Introduction -- Fundamental Concepts in Parametric Inference -- II. Modern Nonparametric Statistical Methods -- Smooth Goodness of Fit Tests -- One-Sample and Two-Sample Problems -- Multi-Sample Problems -- Tests for Trend and Association -- Optimal Rank Tests -- Efficiency -- III. Selected Applications -- Multiple Change-Point Problems -- Bayesian Models for Ranking Data -- Analysis of Censored Data -- A. Description of Data Sets."]
[null,null,null,"Sommario/riassunto","This book demonstrates that nonparametric statistics can be taught from a parametric point of view. As a result, one can exploit various parametric tools such as the use of the likelihood function, penalized likelihood and score functions to not only derive well-known tests but to also go beyond and make use of Bayesian methods to analyze ranking data. The book bridges the gap between parametric and nonparametric statistics and presents the best practices of the former while enjoying the robustness properties of the latter. This book can be used in a graduate course in nonparametrics, with parts being accessible to senior undergraduates. In addition, the book will be of wide interest to statisticians and researchers in applied fields."]