{"product_id":"9781848212893","title":"Nonparametric Tests for Censored Data","description":"\u003ch1\u003eNonparametric Tests for Censored Data\u003c\/h1\u003e\u003ch3\u003eVilijandas Bagdonavicius | Julius Kruopis | Mikhail S. Nikulin\u003c\/h3\u003e\u003cdiv\u003e\u003cb\u003eMathematics \/ Applied\u003c\/b\u003e\u003c\/div\u003e\u003cbr\u003e\u003cdiv\u003e\n\u003cp\u003eStatistical analysis of data sets usually involves construction of a statistical model of the distribution of data within the available sample – and by extension the distribution of all data of the same category in the world. Statistical models are either parametric or non-parametric – this distinction is based on whether or not the model can be described in terms of a finite-dimensional parameter – and the models must be tested to ascertain whether or not they conform to the data, or are accurate.\u003c\/p\u003e \u003cp\u003eThis book addresses the testing of hypotheses in non-parametric models in the specific case of censored or truncated data samples. In particular, the applicability of standard tests to incomplete data sets is considered – for example the use of the chi-squared test for parametric accelerated failure time regression models, which are widely used in reliability, accelerated life testing, and survival analysis, is detailed.\u003c\/p\u003e \u003cp\u003eClassical non-parametric tests (goodness-of-fit, homogeneity, randomness, independence) of censored data are considered, and explained. Tests featured include the chi-squared and modified chi-squared tests, rank and homogeneity tests, and most of the test results are proved, with real applications illustrated using examples. The incorrect use of many tests, and their application using commonly deployed statistical software is highlighted and discussed.\u003c\/p\u003e \u003cp\u003eTheories and exercises are provided, making this book suitable for use in a one semester course in non-parametric statistics and tests.\u003c\/p\u003e\n\u003c\/div\u003e\u003cdiv\u003e  \u003cp\u003e\u003cstrong\u003eVilijandas Bagdonavicius\u003c\/strong\u003e is Professor of Mathematics at the University of Vilnius in Lithuania. His main research areas are statistics, reliability and survival analysis. \u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eJulius Kruopis\u003c\/strong\u003e is Associate Professor of Mathematics at the University of Vilnius in Lithuania. His main research areas are statistics and quality control. \u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eMikhail S. Nikulin\u003c\/strong\u003e is a member of the Institute of Mathematics in Bordeaux, France. \u003c\/p\u003e\n\u003c\/div\u003e\u003cbr\u003e\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublication Date: \u003c\/td\u003e\n\u003ctd\u003e18 January 2011\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublisher: \u003c\/td\u003e\n\u003ctd\u003eWiley\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eImprint: \u003c\/td\u003e\n\u003ctd\u003eWiley-ISTE\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eISBN-13: \u003c\/td\u003e\n\u003ctd\u003e9781848212893\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eFormat: \u003c\/td\u003e\n\u003ctd\u003eHardback\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePage Count: \u003c\/td\u003e\n\u003ctd\u003e233\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eWeight (oz): \u003c\/td\u003e\n\u003ctd\u003e18.08\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":44380416114828,"sku":"9781848212893","price":160.16,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9781848212893_4470d0af-239c-4a32-849c-5a256056970f.jpg?v=1780201577","url":"https:\/\/fh90cf-fv.myshopify.com\/products\/9781848212893","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}