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101.
102.
Roger L. Berger 《Journal of statistical planning and inference》1980,4(4):391-402
Let (X1,…,Xk) be a multinomial vector with unknown cell probabilities (p1,?,pk). A subset of the cells is to be selected in a way so that the cell associated with the smallest cell probability is included in the selected subset with a preassigned probability, P1. Suppose the loss is measured by the size of the selected subset, S. Using linear programming techniques, selection rules can be constructed which are minimax with respect to S in the class of rules which satisfy the P1-condition. In some situations, the rule constructed by this method is the rule proposed by Nagel (1970). Similar techniques also work for selection in terms of the largest cell probability. 相似文献
103.
104.
Mi-Hwa Ko 《统计学通讯:理论与方法》2013,42(8):1553-1562
In this article, the asymmetric Marcinkiewicz-Zygmund strong law of large numbers for linear random field under negative association is obtained. Our result generalizes a result in Gut and Studtmüller (2009). An asymmetric Marcinkiewicz-Zygmund LLN for random fields to the linear random field by using the Beverige-Nelson decomposition. 相似文献
105.
Feng-Shou Ko 《统计学通讯:理论与方法》2013,42(12):2620-2629
For the time-to-event outcome, current methods for sample size determination are based on the proportional hazard model. However, if the proportionality assumption fails to capture the relationship between the hazard time and covariates, the proportional hazard model is not suitable to analyze survival data. The accelerated failure time model is an alternative method to deal with survival data. In this article, we address the issue that the relationship between the hazard time and the treatment effect is satisfied with the accelerated failure time model to design a multi-regional trial for a phase III clinical trial. The log-rank test is employed to deal with the heterogeneous effect size among regions. The test statistic for the overall treatment effect is used to determine the total sample size for a multi-regional trial and the consistent trend is used to rationalize partition sample size to each region. 相似文献
106.
107.
Roger J. Owenα 《统计学通讯:理论与方法》2013,42(5):1035-1052
Interest centres on a group of statisticians , each supplied with the same n sample datapoint sandmaking formal Bayesian inference with a common likelihood function but differing prior knowledge and utility functions. Definitions are proposed which quantify, in a commensurable way, the inference processes of “accuracy”, “confidence” and “consensus” for the case of hypothesis inference with a fixed sample size n. The general significance of comparing the three quantifiers is considered. As n increases the asymptotic behaviour of the quantifiers is evaluated and it is found that the three rates of convergence are of the same order as a function of n. The results are interpreted and some of their implications are discussed. 相似文献
108.
A Monte Carlo simulation is used to study the performance of hypothesis tests for regression coefficients when least absolute value regression methods are used. In small samples, the results of the simulation suggest that using the bootstrap method to compute standard errors will provide improved test performance 相似文献
109.
Roger L. Berger 《The American statistician》2013,67(4):314-318
In this article the problem of comparing two independent binomial populations is considered. It is shown that the test based on the confidence interval p value of Berger and Boos often is uniformly more powerful than the standard unconditional test. This test also requires less computational time. 相似文献
110.
Roger B. Nelsen 《The American statistician》2013,67(4):343-345
The R language, a freely available environment for statistical computing and graphics is widely used in many fields. This “expert-friendly” system has a powerful command language and programming environment, combined with an active user community. We discuss how R is ideal as a platform to support experimentation in mathematical statistics, both at the undergraduate and graduate levels. Using a series of case studies and activities, we describe how R can be used in a mathematical statistics course as a toolbox for experimentation. Examples include the calculation of a running average, maximization of a nonlinear function, resampling of a statistic, simple Bayesian modeling, sampling from multivariate normal, and estimation of power. These activities, often requiring only a few dozen lines of code, offer students the opportunity to explore statistical concepts and experiment. In addition, they provide an introduction to the framework and idioms available in this rich environment. 相似文献