| 书目名称 | Goodness-of-Fit Statistics for Discrete Multivariate Data | | 编辑 | Timothy R. C. Read,Noel A. C. Cressie | | 视频video | | | 丛书名称 | Springer Series in Statistics | | 图书封面 |  | | 描述 | The statistical analysis of discrete multivariate data has received a great deal of attention in the statistics literature over the past two decades. The develop ment ofappropriate models is the common theme of books such as Cox (1970), Haberman (1974, 1978, 1979), Bishop et al. (1975), Gokhale and Kullback (1978), Upton (1978), Fienberg (1980), Plackett (1981), Agresti (1984), Goodman (1984), and Freeman (1987). The objective of our book differs from those listed above. Rather than concentrating on model building, our intention is to describe and assess the goodness-of-fit statistics used in the model verification part of the inference process. Those books that emphasize model development tend to assume that the model can be tested with one of the traditional goodness-of-fit tests 2 2 (e.g., Pearson‘s X or the loglikelihood ratio G ) using a chi-squared critical value. However, it is well known that this can give a poor approximation in many circumstances. This book provides the reader with a unified analysis of the traditional goodness-of-fit tests, describing their behavior and relative merits as well as introducing some new test statistics. The power-divergence family of stati | | 出版日期 | Textbook 1988 | | 关键词 | Chi-squared distribution; Estimator; Likelihood; Variance; best fit; information theory; multinomial distr | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4612-4578-0 | | isbn_softcover | 978-1-4612-8931-9 | | isbn_ebook | 978-1-4612-4578-0Series ISSN 0172-7397 Series E-ISSN 2197-568X | | issn_series | 0172-7397 | | copyright | Springer-Verlag New York Inc. 1988 |
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发表于 2025-3-21 16:29:12
