摘要:

Let {(xi:, Yi:), i = 1, …, n) be the observed data, where xi:is a real vector of lengthkand Yi:, i = 1, …, n a sequence of random variables (r.v.'s). The minimum distance (M.D.) estimators considered here are obtained by minimizing with respect to t the integral dH(y) of the R2norm of the following functionals A-½n[d]i=1:xi:{IYi:-xi:t[d]y] -I[-Yi+ xi:t[d]y]} and A1:½n[d]i=1::(xi:- x)I[Yiy + xit], where A and Al:are matricies such that the inverse of their square root exists. The existence of some of these estimators of thek-dimensional slope parameters under the multiple linear

ISSN:0361-0918    

DOI:10.1080/03610919208813015

出版商:Marcel Dekker, Inc.    

年代:1992

数据来源: Taylor

摘要:

Tables and procedures are given for finding the double sampling plan, conditional double sampling plan, link sampling plan, ChSP-4 and ChSP-4A chain sampling plans involving minimum sum of producer's and consumer's risks for specified Acceptable Quality Level and Limiting Quality Level

ISSN:0361-0918    

DOI:10.1080/03610919208813016

出版商:Marcel Dekker, Inc.    

年代:1992

数据来源: Taylor

摘要:

Suppose n observations are to be taken within a compact region, where the objective is to estimate the mean level of a multidimensional stationary process using the ordinary sample mean as the estimator. Simulated annealing is used to search for optimal (variance minimizing) designs for the case when the observations are correlated. The results give insight into the sensitivity of optimal designs to the strength and nature of the correlation present, extending and reinforcing previous results for the one-dimensional case. An important outcome is that designs which space out the sampling locations evenly are optimal if the correlation is low.

ISSN:0361-0918    

DOI:10.1080/03610919208813017

出版商:Marcel Dekker, Inc.    

年代:1992

数据来源: Taylor

摘要:

Cook (1986) presented the idea of local influence to study the sensitivity of inferences to model assumptions:introduce a vector δ of perturbations to the model; choose a discrepancy function D to measure differences between the original inference and the inference under the perturbed model; study the behavior of D near δ = 0, the original model, usually by taking derivatives. Johnson and Geisser (1983) measure influence in Bayesian inference by the Kullback-Leibler divergence between predictive distributions. I~IcCulloch (1989) is a synthesis of Cook and Johnson and Geisser, using Kullback-Leibler divergence between posterior or predictive distributions as the discrepancy function in Bayesian local influence analyses. We analyze a special case for which McCulloch gives the general theory; namely, the linear model with conjugate prior. We present specific formulae for local influence measures for 1) changes in the parameters of the gamma prior for the precision, 2) changes in the mean of the normal prior for the regression coefficients, 3) changes in the covariance matrix of the normal prior for the regression coefficients and 4) changes in the case weights. Our method is an easy way to find locally influential subsets of points without knowing in advance the sizes of the subsets. The techniques are illustrated with a regression example.

ISSN:0361-0918    

DOI:10.1080/03610919208813018

出版商:Marcel Dekker, Inc.    

年代:1992

数据来源: Taylor

ISSN:0361-0918    

DOI:10.1080/03610919208813004

出版商:Marcel Dekker, Inc.    

年代:1992

数据来源: Taylor