Best minimum bias linear estimators in gauss-markoff model

In this note we present a criterion for linear estimation which is similar to MV-MB-LE of Rao (1978) in Gauss-Markoff model (Y, XB, α²G). We call this criterion MMS-MB-LE (Minimum Mean Square Error-Minimum Bias-Linear Estimation)> Representations of solutions to such estimators similar to those of Rao (1978) are provided.     

On some distributions arising from certain generalized sampling schemes

With the notion of success in a series of trials extended tD refer to a run of like outcomes, several new distributions are obtained as the result of sampling from an urn without replacement. or with additional replacements., In this context, the hy-pergeometric, negative hypergeometric, logarithmic series, generalized Waring, Polya and inverse Polya distributions are extended and their properties are studied     

Bivariate compound poisson distributions

This paper discusses four alternative methods of forming bivariate distributions with compound Poisson marginals. Basic properties of each bivariate version are given. A new bivariate negative binomial distribution, and four bivariate versions of the Sichel distribution, are defined and their properties given.     

The inverse binomial distribution as a statistical model

A particular case of Jain and Consul's (1971) generalized neg-ative binomial distribution is studied. The name inverse binomial is suggested because of its close relation with the inverse Gaussian distribution. We develop statistical properties including conditional inference of a parameter. An application using real data is given.     

Asa Advisory Committees to Federal Statistical Agencies: A Report of the Committee on Committees of the American Statistical Association

(Editor's Note: The following report on ASA advisory committees was prepared by Edwin D. Goldfield as part of a continuing study of the Association's committees and Sections being conducted by the Committee on Committees. Because of the importance of advisory committees to Federal agencies, the report is included here for the information of the members of the Association.)     

Least Squares Programs-A Look at the Square Root Procedure

Various algorithms are in use on computers to solve least squares problems. Apparently very few programs use the square root procedure. In this paper, results from programs based on the square root procedure are compared with results based on some other algorithms. Remarkably good results are obtained using the square root procedure.     

Identities and inequalities for the expected values of random matrices and loewner's theory

We consider the identity associated with the expected values of the matrix-valued quadratic forms of two random matrices. As a special case the identity yields the matrix-valued inequality of the Schwarz type. The most important application is for Loewner's theory in the context of the operator-monotone function, and the inequalities based on the concavityconvexity of the matrix-valued functions are derived.     

Estimating the minimum and maximum location parameters for two ig-exponential scale mixtures

Suppose that we have two components, each having a two-parameter exponential distribution. Suppose further that these components are conditionally independent, sharing a common random hazard rate and possessing unequal, fixed, unknown location parameters. We develop estimators for the minimum and maximum of these location parameters when the random hazard rate has an inverse Gaussian distribution. Performance comparisons are made among the proposed estimators. Maximum likelihood estimators are shown to be inadmissible.     

用淬冷法确定饱和液氮中的池沸腾热流密度曲线

用直径为５０ｍｍ、厚度为１２ｍｍ的铜平板在液氮中进行了不同热面方位角的淬冷沸腾实验，各方位角为θ＝０°（热面向下）、１０°、２０°、３０°、５０°和９０°（热面垂直）；随着方位角的增加，临界热流密度、最小膜态沸腾热流密度及其壁面过热度相应地增加，且在方位角θ＜３０°时，θ对上述参数的影响更大；得出ｑＣＨＦ、ｑｍｉｎ与方位角的关系式．     

Tests for outliers in the inverse Gaussian distribution,with application to first hitting time models

The inverse Gaussian (IG) distribution is often applied in statistical modelling, especially with lifetime data. We present tests for outlying values of the parameters (μ, λ) of this distribution when data are available from a sample of independent units and possibly with more than one event per unit. Outlier tests are constructed from likelihood ratio tests for equality of parameters. The test for an outlying value of λ is based on an F-distributed statistic that is transformed to an approximate normal statistic when there are unequal numbers of events per unit. Simulation studies are used to confirm that Bonferroni tests have accurate size and to examine the powers of the tests. The application to first hitting time models, where the IG distribution is derived from an underlying Wiener process, is described. The tests are illustrated on data concerning the strength of different lots of insulating material.