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Titlebook: Statistical Methods for Ranking Data; Mayer Alvo,Philip L.H. Yu Book 2014 Springer Science+Business Media New York 2014 Block designs.Expl

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發(fā)表于 2025-3-21 17:58:20 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Statistical Methods for Ranking Data
編輯Mayer Alvo,Philip L.H. Yu
視頻videohttp://file.papertrans.cn/877/876526/876526.mp4
概述Contains a unified treatment of both inference and modeling for ranking data.Contains comprehensive software to enable the practitioner to access the methods.Contains illustrative data sets and exerci
叢書名稱Frontiers in Probability and the Statistical Sciences
圖書封面Titlebook: Statistical Methods for Ranking Data;  Mayer Alvo,Philip L.H. Yu Book 2014 Springer Science+Business Media New York 2014 Block designs.Expl
描述.This book introduces advanced undergraduate, graduate students and practitioners to statistical methods for ranking data. An important aspect of nonparametric statistics is oriented towards the use of ranking data. Rank correlation is defined through the notion of distance functions and the notion of compatibility is introduced to deal with incomplete data. Ranking data are also modeled using a variety of modern tools such as CART, MCMC, EM algorithm and factor analysis..This book deals with statistical methods used for analyzing such data and provides a novel and unifying approach for hypotheses testing. The techniques described in the book are illustrated with examples and the statistical software is provided on the authors’ website..
出版日期Book 2014
關(guān)鍵詞Block designs; Exploratory data analysis; Missing and tied data; Probabilistic and statistical modeling
版次1
doihttps://doi.org/10.1007/978-1-4939-1471-5
isbn_softcover978-1-4939-4781-2
isbn_ebook978-1-4939-1471-5Series ISSN 2624-9987 Series E-ISSN 2624-9995
issn_series 2624-9987
copyrightSpringer Science+Business Media New York 2014
The information of publication is updating

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發(fā)表于 2025-3-21 21:26:11 | 只看該作者
Correlation Analysis of Paired Ranking Data, then be thought of as a permutation of the integers .. We may denote such a permutation by .?=?(.(1),?.(2),?.,?.(.))′ which may also be conceptualized as a point in t-dimensional space. It is natural to measure the spread between two individual permutations .,?. by means of a distance function.
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Statistical Methods for Ranking Data978-1-4939-1471-5Series ISSN 2624-9987 Series E-ISSN 2624-9995
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發(fā)表于 2025-3-22 11:47:34 | 只看該作者
Exploratory Analysis of Ranking Data,Descriptive statistics present an overall picture of ranking data. Not only do they provide a summary of the ranking data, but they are also often suggestive of the appropriate direction to analyze the data. Therefore, it is suggested that researchers consider descriptive analysis prior to any sophisticated data analysis.
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發(fā)表于 2025-3-22 14:54:12 | 只看該作者
Mayer Alvo,Philip L.H. YuContains a unified treatment of both inference and modeling for ranking data.Contains comprehensive software to enable the practitioner to access the methods.Contains illustrative data sets and exerci
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Book 2014arametric statistics is oriented towards the use of ranking data. Rank correlation is defined through the notion of distance functions and the notion of compatibility is introduced to deal with incomplete data. Ranking data are also modeled using a variety of modern tools such as CART, MCMC, EM algo
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