Fundamentals of Mathematical Statistics: Statistical Inference: Springer Texts in Statistics
Autor Hung T. Nguyen, Gerald S. Rogersen Limba Engleză Paperback – 21 oct 2011
| Toate formatele și edițiile | Preț | Express |
|---|---|---|
| Paperback (2) | 381.34 lei 6-8 săpt. | |
| Springer – 21 oct 2011 | 381.34 lei 6-8 săpt. | |
| Springer – 12 oct 2012 | 381.72 lei 6-8 săpt. | |
| Hardback (1) | 391.54 lei 6-8 săpt. | |
| Springer – 25 iul 1989 | 391.54 lei 6-8 săpt. |
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Specificații
ISBN-13: 9781461389163
ISBN-10: 146138916X
Pagini: 440
Ilustrații: XI, 422 p.
Dimensiuni: 155 x 235 x 23 mm
Greutate: 0.61 kg
Ediția:Softcover reprint of the original 1st ed. 1989
Editura: Springer
Colecția Springer
Seria Springer Texts in Statistics
Locul publicării:New York, NY, United States
ISBN-10: 146138916X
Pagini: 440
Ilustrații: XI, 422 p.
Dimensiuni: 155 x 235 x 23 mm
Greutate: 0.61 kg
Ediția:Softcover reprint of the original 1st ed. 1989
Editura: Springer
Colecția Springer
Seria Springer Texts in Statistics
Locul publicării:New York, NY, United States
Public țintă
ResearchCuprins
IV: Sampling and distributions.- Overview.- Lesson 1 Sampling and statistics.- 2 Transformations of real random variables.- 3 Transformations of random vectors.- 4 Sampling distributions in normal populations-I.- 5 Sampling distributions in normal populations-II.- 6 Order statistics.- 7 Sufficient statistics-I.- 8 Sufficient statistics-II.- 9 Complete statistics.- 10 Exponential families-I.- 11 Exponential families-II.- V: Statistical estimation.- Overview.- Lesson 1 Point estimation of parameters.- 2 Conditional expectation.- 3 Uniformly minimum variance unbiased estimators.- 4 Efficient estimators.- 5 Unbiased estimation: the vector case.- 6 Two methods of point estimation.- 7 Maximum likelihood estimation.- 8 Confidence interval estimation-I.- 9 Confidence interval estimation-II.- 10 Consistent estimators.- 11 Consistency of maximum likelihood estimators.- 12 Asymptotic normality.- 13 Asymptotic normality of maximum likelihood estimators.- 14 Asymptotic efficiency and large sample confidence intervals.- VI: Testing hypotheses.- Overview.- Lesson 1 Neyman-Pearson theory-I.- 2 Neyman-Pearson theory-II.- 3 Testing with monotone likelihood ratios.- 4 Testing when the support contains parameters.- 5 Unbiased tests.- 6 Quadratic forms in normal random variables.- 7 Likelihood ratio tests-I.- 8 One-way analysis of variance.- 9 Likelihood ratio tests-II.- 10 LRT-asymptotic distributions.- 11 Summary of tests for normal populations.- 12 Tests for two-by-two tables.- VII: Special topics.- Overview.- Lesson 1 Minimax and Bayes estimators-I.- 2 Minimax and Bayes estimators-II.- 3 Equivariant estimators.- 4 Simple linear regression-I.- 5 Simple linear regression-II.- 6 Sufficient statistics and uniformly most powerful tests.- 7 Sequential probability ratio tests.- 8 A test by Mann, Whitney, Wilcoxon.- 9 Tests for paired comparisons.- 10 Tests of Kolmogorov, Smirnov type.- 11 Categorical data.- Tables.- References.
Recenzii
"This two-volume text is designed for a two-semester course in mathematical statistics at the senior/graduate level... The authors have succeeded in presenting the material with clarity and enough details of analytical niceties." (Mathematical Reviews)