<p>Statistical Distributions (3 edition) by Merran Evans , Nicholas Hastings , Brian Peacock<br/>这是一本很好的参考书. 包括了基本的统计分布函数.<br/><br/>得益于这个论坛很久了,也想做一点小贡献 <img title="人大经济论坛 http://www.pinggu.org" alt="图片点击可在新窗口打开查看" src="http://www.pinggu.name/bbs/Skins/Default/emot/em01.gif" align="middle" border="0"/>&nbsp; <br/></p><p>
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<br/><br/>【书名】 Statistical Distributions <br/>【作者】Merran Evans , Nicholas Hastings , Brian Peacock <br/>【出版社】Wiley-Interscience<br/>【版本】3 edition<br/>【出版日期】June 15, 2000<br/>【文件格式】PDF<br/>【文件大小】9.3M<br/>【页数】221 pages<br/>【ISBN出版号】<b>ISBN-10:</b> 0471371246 <b>ISBN-13:</b> 978-0471371243<br/>【资料类别】统计学 <br/>【市面定价】$76.45 (美元)<br/>【扫描版还是影印版】清晰扫描版<br/>【是否缺页】是<br/>【关键词】power function variate, variate corresponds, rectangular variate, Parameter Estimator Method, Biometrika Trustees<br/>【内容简介】* Presents the 40 distributions in alphabetical order<br/>* Provides all key formulas for each distribution<br/>* Adds a new chapter on the Empirical Distribution Function<br/>* Expands the Weibull Distribution to cover the 3 and 5 parameter versions<br/>* Incorporates diagrams and tables illustrating the characteristics of each distribution<br/>* Discusses the types of application for which distributions are used<br/>* Features references to relevant software packages<br/><br/>【目录】Contents<br/>Preface<br/>1. Introduction<br/>2. Terms and Symbols<br/>2.1 Probability, Random Variable, Variate, and<br/>Random Number, 3<br/>2.2 Range, Quantile, Probability Statements and<br/>Domain, and Distribution Function, 5<br/>2.3 Inverse Distribution and Survival Function, 8<br/>2.4 Probability Density Function and Probability<br/>Function, 9<br/>2.5 Other Associated Functions and Quantities, 11<br/>3. General Variate Relationships 17<br/>3.1 Introduction, 17<br/>3.2 Function of a Variate, 17<br/>3.3 One-to-one Transformations and Inverses, 18<br/>3.4 Variate Relationships Under One-to-one<br/>Transformation, 20<br/>3.5 Parameters, Variate, and Function Notation, 22<br/>3.6 Transformation of Location and Scale, 24<br/>3.7 Transformation from the Rectangular Variate, 25<br/>3.8 Many-to-One Transformations, 26<br/>3.9 Functions of Several Variates, 29<br/>4. Bernoulli Distribution<br/>4.1 Random Number Generation, 32<br/>4.2 Curtailed Bernoulli Trial Sequences, 32<br/>4.3 Urn Sampling Scheme, 33<br/>4.4 Note, 33<br/>5. Beta Distribution<br/>5.1 Notes on Beta and Gamma Functions, 35<br/>5.2 Variate Relationships, 37<br/>5.3 Parameter Estimation, 40<br/>5.4 Random Number Generation, 41<br/>5.5 Inverted Beta Distribution, 41<br/>5.6 Noncentral Beta Distribution, 42<br/>5.7 Beta Binomial Distribution, 42<br/>6. Binomial Distribution<br/>6.1 Variate Relationships, 44<br/>6.2 Parameter Estimation, 46<br/>6.3 Random Number Generation, 47<br/>7. Cauchy Distribution<br/>7.1 Note, 49<br/>7.2 Variate Relationships, 49<br/>7.3 Random Number Generation, 50<br/>7.4 Generalized Form, 50<br/>8. Chi-Squared Distribution<br/>8.1 Variate Relationships, 53<br/>8.2 Random Number Generation, 57<br/>8.3 Chi Distribution, 57<br/>9. Chi-Squared (Noncentral) Distribution<br/>9.1 Variate Relationships, 59<br/>10. Dirichlet Distribution<br/>10.1 Variate Relationships, 62<br/>10.2 Dirichlet Multinomial Distribution, 63<br/>11. Empirical Distribution Function<br/>11.1 Estimation from Uncensored Data, 65<br/>11.2 Estimation from Censored Data, 66<br/>11.3 Parameter Estimation, 67<br/>11.4 Example, 67<br/>11.5 Graphical Method for the Modified Order-<br/>Numbers, 69<br/>11.6 Model Accuracy, 70<br/>12. Erlang Distribution<br/>12.1 Variate Relationships, 72<br/>12.2 Parameter Estimation, 73<br/>12.3 Random Number Generation, 73<br/>13. Error Distribution<br/>13.1 Note, 75<br/>13.2 Variate Relationships, 76<br/>14. Exponential Distribution<br/>14.1 Note, 79<br/>14.2 Variate Relationships, 80<br/>14.3 Parameter Estimation, 81<br/>14.4 Random Number Generation, 81<br/>15. Exponential Family<br/>15.1 Members of the Exponential Family, 82<br/>15.2 Univariate One-Parameter Exponential<br/>Family, 82<br/>15.3 Estimation, 84<br/>16. Extreme Value (Gumbel) Distribution<br/>16.1 Note, 86<br/>16.2 Variate Relationships, 86<br/>16.3 Parameter Estimation, 89<br/>16.4 Random Number Generation, 89<br/>17. F (Variance Ratio) or Fisher-Snedecor Distribution<br/>17.1 Variate Relationships, 91<br/>18. F (Noncentral) Distribution<br/>18.1 Variate Relationships, 96<br/>19. Gamma Distribution<br/>19.1 Variate Relationships, 99<br/>19.2 Parameter Estimation, 101<br/>19.3 Random Number Generation, 102<br/>19.4 Inverted Gamma Distribution, 103<br/>19.5 Normal Gamma Distribution, 103<br/>19.6 Generalized Gamma Distribution, 104<br/>20. Geometric Distribution<br/>20.1 Notes, 107<br/>20.2 Variate Relationships, 108<br/>20.3 Random Number Generation, 108<br/>21. Hypergeometric Distribution<br/>21.1 Note, 111<br/>21.2 Variate Relationships, 11 1<br/>21.3 Parameter Estimation, 112<br/>21.4 Random Number Generation, 112<br/>21.5 Negative Hypergeometric Distribution, 112<br/>21.6 Generalized Hypergeometric (Series)<br/>Distribution, 113<br/>22. Inverse Gaussian (Wald) Distribution<br/>22.1 Variate Relationships, 115<br/>22.2 Parameter Estimation, 116<br/>23. Laplace Distribution<br/>23.1 Variate Relationships, 118<br/>23.2 Parameter Estimation, 120<br/>23.3 Random Number Generation, 120<br/>24. Logarithmic Series Distribution<br/>24.1 Variate Relationships, 122<br/>24.2 Parameter Estimation, 122<br/>25. Logistic Distribution<br/>25.1 Notes, 126<br/>25.2 Variate Relationships, 127<br/>25.3 Parameter Estimation, 128<br/>25.4 Random Number Generation, 128<br/>26. Lognormal Distribution<br/>26.1 Variate Relationships, 130<br/>26.2 Parameter Estimation, 133<br/>26.3 Random Number Generation, 133<br/>27. Multinomial Distribution<br/>27.1 Variate Relationships, 136<br/>27.2 Parameter Estimation, 136<br/>28. Multivariate Normal (Multinormal) Distribution<br/>28.1 Variate Relationships, 138<br/>28.2 Parameter Estimation, 139<br/>xii<br/>29. Negative Binomial Distribution<br/>29.1 Note, 142<br/>29.2 Variate Relationships, 142<br/>29.3 Parameter Estimation, 144<br/>29.4 Random Number Generation, 144<br/>30. Normal (Gaussian) Distribution<br/>30.1 Variate Relationships, 146<br/>30.2 Parameter Estimation, 150<br/>30.3 Random Number Generation, 150<br/>31. Pareto Distribution<br/>31.1 Note, 153<br/>31.2 Variate Relationships, 153<br/>31.3 Parameter Estimation, 154<br/>31.4 Random Number Generation, 154<br/>32. Poisson Distribution<br/>32.1 Note, 157<br/>32.2 Variate Relationships, 157<br/>32.3 Parameter Estimation, 160<br/>32.4 Random Number Generation, 160<br/>33. Power Function Distribution<br/>33.1 Variate Relationships, 162<br/>33.2 Parameter Estimation, 164<br/>33.3 Random Number Generation, 164<br/>34. Power Series (Discrete) Distribution<br/>34.1 Note, 166<br/>34.2 Variate Relationships, 166<br/>33.3 Parameter Estimation, 166<br/>35. Rayleigh Distribution<br/>35.1 Variate Relationships, 168<br/>35.2 Parameter Estimation, 169<br/>36. Rectangular (Uniform) Continuous Distribution<br/>36.1 Variate Relationships, 171<br/>36.2 Parameter Estimation, 174<br/>36.3 Random Number Generation, 174<br/>37. Rectangular (Uniform) Discrete Distribution<br/>37.1 General Form, 176<br/>37.2 Parameter Estimation, 177<br/>38. Student's t Distribution<br/>38.1 Variate Relationships, 180<br/>38.2 Random Number Generation, 183<br/>39. Student's t (Noncentral) Distribution<br/>39.1 Variate Relationships, 186<br/>40. Triangular Distribution<br/>40.1 Variate Relationships, 188<br/>40.2 Random Number Generation, 188<br/>41. von Mises Distribution<br/>41.1 Note, 190<br/>41.2 Variate Relationships, 191<br/>41.3 Parameter Estimation, 191<br/>42. Weibull Distribution<br/>42.1 Note, 193<br/>42.2 Variate Relationships, 194<br/>42.3 Parameter Estimation, 194<br/>42.4 Random Number Generation, 196<br/>42.5 Three-Parameter Weibull Distribution, 196<br/>42.6 Three-Parameter Weibull Random Number<br/>Generation, 197<br/>42.7 Bi-Weibull Distribution. 197<br/>xiii<br/>170<br/>xiv<br/>42.8 Five-Parameter Bi-Weibull Distribution, 199<br/>42.9 Weibull Family, 202<br/>43. Wishart (Central) Distribution<br/>43.1 Note, 205<br/>43.2 Variate Relationships, 205<br/>INDEX<br/>44. Computing References 206<br/>45. Statistical Tables 210<br/>45.1 Normal Distribution Function, 211<br/>45.2 Percentiles of the Chi-Squared Distribution, 212<br/>45.3 Percentiles of the F Distribution, 214<br/>45.4 Percentiles of the Student's t Distribution, 218<br/>45.5 Partial Expectations for the Standard Normal<br/>Distribution, 219<br/>Bibliography 220<br/>【书评】整理书评】Provides a concise summary of facts and formulas relating to 40 major<br/>probability distributions, together with associated diagrams that allow<br/>the shape and other general properties of each distribution to be<br/>readily appreciated. Introductory chapters cover fundamental concepts<br/>and describe rules governing relationships between variates. Extensive<br/>use is made of the inverse distribution function. This third edition<br/>includes more distributions and new material on applications, variate<br/>relationships, estimation, and computing. Evans is Director of Planning<br/>and Academic Affairs at Monash University, Australia.</p><br/>
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