论文检索

概率与数理统计导论AI 解读

Probability Random Variables and Their Distributions Special Probability Distributions Joint Distributions Properties of Random Variables Functions of Random Variables Limiting Distributions Statistics and Sampling Distributions Point Estimation Sufficiency and Completeness Interval Estimation Test of Hypotheses Contingency Tables and Goodness-of-Fit Nonparametric Methods Regression and Linear Models Reliability and Survival Distributions Answers to Selected Exercises.

关于 Gamma 分布均值的推断AI 解读

Approximate tests for the mean of a gamma distribution with both parameters unknown are derived. The power of these tests is close to the power of the corresponding uniformly most powerful tests for the mean when the shape parameter is assumed known. The tests are studied by Monte Carlo simulation, and limiting results are also provided as the shape parameter goes to zero or infinity, as well as for the large-sample case. A limited study indicating the nonrobustness of the…

Ⅰ型删失抽样下双参数指数分布的统计推断AI 解读

Inferences concerning the location and scale parameters of an exponential distribution are discussed for samples censored at a fixed value. The procedures considered are uniformly most powerful unbiased if the tests are performed with replacement and they seem to be quite reasonable when testing without replacement.

某对数统计量的双矩卡方近似（表达式缺失）AI 解读

A two-moment chi-square approximation is derived for the statistic log , where and are, respectively, the arithmetic and geometric means of a sample from a gamma distribution. The proposed approximation is used for testing the shape parameter in a gamma distribution and for testing the homogeneity of normal population variances.

摘要暂缺

双变量指数分布参数的估计与假设检验AI 解读

Statistical properties of the bivariate exponential distribution are investigated. Maximum likelihood and method of moments type estimates are obtained and compared with the estimates given by Arnold. The method of moments type estimates are easy to compute and highly efficient, whereas the maximum likelihood estimates are computationally inconvenient. The problem of testing for correlation in the bivariate exponential distribution is also investigated.