Counterexamples in Probability And StatisticsCRC Press, 01/06/1986 - 328 من الصفحات This volume contains six early mathematical works, four papers on fiducial inference, five on transformations, and twenty-seven on a miscellany of topics in mathematical statistics. Several previously unpublished works are included. |
المحتوى
CHAPTER | 1 |
A | 4 |
A | 5 |
A | 6 |
An infinite sequence of events such that every pair is independent but no triple | 7 |
A | 8 |
A | 9 |
4 | 12 |
6 | 163 |
Construction of Estimators | 175 |
CHAPTER NINE | 190 |
48 | 230 |
Hypothesis Testing | 232 |
An unreasonable level 0 05 test result | 238 |
7 | 243 |
Additional Counterexamples | 267 |
CHAPTER | 23 |
CHAPTER THREE | 38 |
CHAPTER FOUR | 53 |
5 | 57 |
Sequences of Random Variables | 83 |
symmetric distribution | 106 |
CHAPTER | 126 |
Properties of Statistical Experiments | 154 |
Bayes methods | 273 |
Admissibility | 274 |
Hypothesis testing | 275 |
Confidence intervals 276 A 13 Categorical data analysis | 276 |
A 14 | 277 |
| 278 | |
| 287 | |
طبعات أخرى - عرض جميع المقتطفات
عبارات ومصطلحات مألوفة
asymptotically Borel-Cantelli Lemma Cauchy distribution characteristic function Consider converge almost surely converges in distribution converges in probability countable counterexample cumulative distribution function defined density function discrete probability function distributed random variables distribution with mean equal equivariant estimator exponential family family of distributions finite follows given hypothesis H inadmissible independent and identically independent random variables infinite Lebesgue measure Lehmann Lemma martingale maximum likelihood estimator mean squared error mean zero method of moments minimal sufficient minimum variance unbiased monotone likelihood ratio Note null hypothesis o-field pairwise independent parameter powerful invariant test powerful test powerful unbiased test probability measure probability space real numbers real random variable rejects for large risk sequence of independent sequence of random standard Gaussian distribution submartingale subset sufficient statistic Theorem uniformly minimum variance uniformly most powerful unique variables that converges variance unbiased estimator Y₁ Y₂ σ²
مقاطع مشهورة
الصفحة 279 - Inadmissibility of the Usual Estimators of Scale Parameters in Problems with Unknown Location and Scale Parameters . . LAWRENCE D.
الصفحة 278 - BARANCHIK, AJ (1973) : Inadmissibility of maximum likelihood estimators in some multiple regression problems with three or more independent variables, Ann.
الصفحة xvii - Here, standardization was achieved through a change of random variables by subtracting the mean and dividing by the standard deviation of the original random variable.
الصفحة 279 - McGill. 1983. A color-caused optical illusion on a statistical graph.