Page 675 - Probability and Statistical Inference
P. 675

652    Index

                                 455                               Convex function 152-156
                                 Confidence region 463                Jensen’s inequality 154
                                     Mean vector 463-465           Convolutions 185-187
                                     Multiple comparisons 465-469,  Cornish-Fisher expansion 267-268
                                     475-476                          F percentage point 269-270
                                     Multivariate F distribution 468-
                                     469                              t percentage point 267-268
                                     Multivariate t distribution 466  Correlation coefficient 121
                                 Continuous random variables 23       Confidence interval 563
                                 Continuous uniform distribution 37,  Sample correlation 216
                                     38                               Tests of hypotheses 560-563
                                 Convergence notions 241              Zero correlation and indepen-
                                     Central limit theorem (CLT)      dence 139-141, 171-172
                                     257                           Counting rules 16
                                     In distribution or law 253       Combinations 16
                                     In probability 242               Permutations 16
                                     Weak law of large numbers
                                     (WLLN) 241-242                Covariance 119
                                 Convergence results 264-270       Covariance inequality 150; see also
                                     Central limit theorem (CLT)      Cauchy-Schwarz inequality
                                     257                              Applications 122-123, 368
                                       Sample mean 258             Cramér-Rao lower bound (CRLB)
                                       Sample variance 262            366
                                     Chi-square distribution 264      Attainment 368-369
                                     Dominated convergence            Non-attainment 369-371
                                     theorem 274                      Non-iid case 374-375
                                     F distribution 265            Cramér-Rao inequality 366
                                     Khinchine’s WLLN 245, 270
                                       Sample variance 251-252        Information 368
                                     Mann-Wald Theorem 261, 275       Minimum variance unbiased
                                     Monotone convergence theo-       estimator (MVUE) 369-370
                                     rem 71, 92, 274                  Non-iid case 374-375
                                     Multivariate F distribution 279-  Sufficiency 375-377
                                     280                           Credible interval 478, 488
                                     Multivariate t distribution 279-  Contrast with confidence
                                     280                              intervals 492-493
                                     Probability density function     Highest posterior density (HPD)
                                       F distribution 209-211, 267-
                                     268                              489-492
                                       t distribution 207-209, 265-  Credible sets 488
                                     266                           Critical function 399
                                     Percentage points             Critical region 397-399
                                       F distribution 268-270      Cumulative distribution function
                                       t distribution 266-267         (cdf); see Distribution function
                                     Slutsky’s Theorem 257, 260-      (df)
                                     263                           Curved exponential family 144, 335
                                     Weak law of large numbers
                                     (WLLN) 241-242                              D
                                     Weak WLLN 242-244, 270        DeMorgan’s Law 5, 11, 51
                                       Sample variance 251-252,    Derivative of integral 29, 30
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