To Pool or Not to Pool: The Quality Bank Case

Drawing on a recent hearing before the Federal Energy Regulatory Commission, this article illustrates how two statisticians on opposing sides, using two different approaches to the problem, arrived at the same estimator. The differences between the two approaches are highlighted and a proof for the equivalence of the two estimators is given.     

Goodness of exact experimental designs with respect to a certain family of criteria

In the paper we assume to be given an approximate optimum exact design with respect to one optimality criterion. We investigate the goodness of this design in the sense of a family of criteria that includes those of A-E-, and .D-optimality.     

Sequential analysis applied to testing the scale parameter in the problem of the nile

The parameter O in the problem of the Nile is tested using the Sequential Probability Ratio Test (SPRT). It is observed that the test can be used to discriminate between two one–sided hypotheses.     

唐代试律的套式

现存唐代应试律诗可根据尾联结句方式的不同分为祈请式、颂圣式、怅怨式和闲淡式等四种套式,这些套式既是唐代试律程式化的主要表征,也是后人讥评其＂体卑＂的一大原因。唐代试律套式的形成与试诗题目限制、格式要求及特殊的应试环境有关,同时与唐代文士包括知贡举者和赴举士子对试律本身并不十分看重的主观因素密切关联。     

Testing linear inequality constraints in the standard linear model

In this paper we are concerned with the problem of testing whether the â-parameters of the standard linear model satisfy the linear equality constraints R = r when they are known to satisfy the corresponding linear inequality constraints Râ ? r. In particular we will show that the exact finite sample null distributions of the Likelihood Ratio, Wald and Kuhn-Tucker

statistics are known when R is of full row rank but not known when R has less than full row rank. The less than full row rank problem has not been discussed previously but it is of considerable potential importance.

This paper contains several simple numerical examples which illustrate the computational details of the tests     

A class of test statistics for testing whether new is better than used

A class of test statistics Is proposed for testing that a life distribution Is exponential against that it is new better than used and not exponential, Consistency, unbiasedness and the asymptotic normality for the one class of class of test are proved. The efflication are compeled and compared with some otner statinties. The proposed test is shown to perform well against other tests.     

Linear rank tests for censored survival data

We describe a class of rank test procedures for the two-sample problem with right censored survival data. The class of tests is directly generalized from the linear rank tests by assigning each observation a rank according to its corresponding Wilcoxon scores. It allows a flexible choice of score functions, in particular, those powerful against scale differences between the two survival distributions. Monte Carlo simulations have shown that some members of this class have great power in detecting crossing-curve alternatives (alternatives where underlying survival curves cross over). The class also contains tests essentially equivalent to the Gehan-Wilcoxon and the logrank tests.     

On choosing between two nonlinear models estimated robustly. Some Monte Carlo evidence

The article considers the problem of choosing between two (possibly) nonlinear models that have been fitted to the same data using M-estimation methods. An asymptotically normally distributed test statistic that takes into account the fact that the models are fitted robustly is given. The new procedure is compared with other test statistics using a Monte Carlo study. We found that the presence of a competitive model either in the null or the alternative hipothesis affects the distributional properties of the tests, and that in the case that the data contains outlying observations the new procedure had a significantly higher power than the rest of the tests.     

On level and powee of anderson and hauck's peocedure for testing equivalence in compative bioavailability

The paper refers to a new procedure of Anderson and Hauck for the well-known problem of deciding whether two means of normal distributions with common but unknown variance differ within an admissible range. Analytical expressions for level and power of this method are derived and some numerical examples are given. A bound for the difference between real and no¬minal level is obtained which does not involve the variance.