摘要:

We propose a simple and efficient way to approximate multivariate normal probabilities using univariate and bivariate probabilities. The approximation is computationally tested for the trivariate and quadrivariate normal probabilities. A few problems of higher dimensions were also tested.

ISSN:0361-0918    

DOI:10.1080/03610919008812873

出版商:Marcel Dekker, Inc.    

年代:1990

数据来源: Taylor

摘要:

There are two basic approaches for examining the contribution of in-dividual variables to separation of groups after rejection of a multivariate hypothesis: (1) a multivariate approach showing the contribution of each variable in the presence of the other variables, and (2) a univariate approach showing the contribution of each variable by itself ignoring the other vari-ables. For the multivariate approach, we express the standardized (canonical) discriminant function coefficients in a form showing that the contribution of each variable is due to its multiple correlation with the other variables and how well its separation of groups can be predicted from the other variables. For the univariate approach, we present the results of a Monte Carlo study comparing four methods of testing individual variables. A “protected” pro-cedure that performsFtests only if the overall Wilks' A rejects, appears to be preferred.

ISSN:0361-0918    

DOI:10.1080/03610919008812874

出版商:Marcel Dekker, Inc.    

年代:1990

数据来源: Taylor

摘要:

Properties and relationships of some commonly used probability bounds, along with other recently developed bounds and approximations, are evaluated for their performance with pairwise comparisons. The comparisons are of independent sample means obtained from normal random variables with a common variance. Computational methods are presented and numerical results are used to further evaluate the performance of the bounds.

ISSN:0361-0918    

DOI:10.1080/03610919008812875

出版商:Marcel Dekker, Inc.    

年代:1990

数据来源: Taylor

摘要:

We obtain exact tables of the null distribution of Spearman's footrule for sample sizes n = 4(1)40 by using a certain Markov chain property, and we investigate the adequacy of approximations to the distribution.

ISSN:0361-0918    

DOI:10.1080/03610919008812876

出版商:Marcel Dekker, Inc.    

年代:1990

数据来源: Taylor

摘要:

The univariate changepoint problem has been extensively studied in the literature. Several investigators have developed test statistics and estimators (both parametric and nonparametric) in classical and Bayesian frameworks. Extensions to multivariate changepoint problems have also been considered. Most such papers have assumed that the variables have continuous distributions. In our study we consider the at most one changepoint(AMOC) problem in a sequence of multinomial random variables. Three estimators to detect a possible change in the sequence are proposed. The results of a Monte Carlo simulation study of the estimators are presented.

ISSN:0361-0918    

DOI:10.1080/03610919008812877

出版商:Marcel Dekker, Inc.    

年代:1990

数据来源: Taylor

摘要:

Statistical comparisons of several nonparametric changepoint estimators which are currently offered in the literature are undertaken. The criteria for comparison are Pitman nearness, probability concentration and mean squared error. Recommendations for small, moderate and large sample cases are given.

ISSN:0361-0918    

DOI:10.1080/03610919008812878

出版商:Marcel Dekker, Inc.    

年代:1990

数据来源: Taylor

摘要:

A well-known estimator for the shape parameter of a two-parameter Weibull distribution from a failure-censored sample involves a preliminary test of àa null hypothesis concerning the parameter. Efficiency of the resulting testimator varies with the chosen level of significance of the test. We present an alternative procedure with a higher efficiency over this for each significance level under various circumstances. Appropriate choice of significance level is also discussed.

ISSN:0361-0918    

DOI:10.1080/03610919008812879

出版商:Marcel Dekker, Inc.    

年代:1990

数据来源: Taylor

摘要:

This paper presents the results of comparative tests of several random number generators to generate uniform [0,1] pseudo-random numbers. Tests were run on two different kinds of microcomputers with similar results. The computers used were a Tandy Model 4D (an 8 bit machine) and a Zenith model 150 (a 16 bit IBM compatible machine operating under MS DOS 2.11 and 3.1) withouta math coprocessor chip. All programming was done in FORTRAN using the Microsoft FORTRAN compilers available for the two machines (two MS DOS compilers were used; Microsoft's FORTRAN 77, versions 3.2 and 4.0).

ISSN:0361-0918    

DOI:10.1080/03610919008812880

出版商:Marcel Dekker, Inc.    

年代:1990

数据来源: Taylor

摘要:

Mee, Eberhardt, and Reeve (1989) recently produced tables of factors for simultaneous two-sided tolerance intervals for linear regression. These factors, obtained using numerical quadrature, provide narrower intervals than were previously available. Using identical notation, this article presents simultaneous one-sided tolerance limits for regression models. Since one-sided tolerance limits are equivalent to one-sided confidence limits on percentiles, the bounds proposed here provide simultaneous one-sided confidence limits for a specified percentile of the conditional distributions of the dependent variable. Although this specific problem had not been addressed previously in the literature, several authors have proposed simultaneous two-sided confidence intervals for a specified percentile of the dependent variable in regression (Steinhorst and Bowden 1971 ; Thomas and Thomas 1986; Turner and Bowden 1977). The limits proposed here have several applications to calibration (or discrimination). For example, one use is the construction of one-sided confidence limits for future unobserved values of the independent variable. The analogous two-sided inference in calibration has been discussed by Lieberman, Miller and Hamilton (1967) and Scheffe' (1973).

ISSN:0361-0918    

DOI:10.1080/03610919008812881

出版商:Marcel Dekker, Inc.    

年代:1990

数据来源: Taylor

摘要:

An imputation procedure is a procedure by which each missing value in a data set is replaced (imputed) by an observed value using a predetermined resampling procedure. The distribution of a statistic computed from a data set consisting of observed and imputed values, called a completed data set, is affecwd by the imputation procedure used. In a Monte Carlo experiment, three imputation procedures are compared with respect to the empirical behavior of the goodness-of- fit chi-square statistic computed from a completed data set. The results show that each imputation procedure affects the distribution of the goodness-of-fit chi-square statistic in 3. different manner. However, when the empirical behavior of the goodness-of-fit chi-square statistic is compared u, its appropriate asymptotic distribution, there are no substantial differences between these imputation procedures.

ISSN:0361-0918    

DOI:10.1080/03610919008812882

出版商:Marcel Dekker, Inc.    

年代:1990

数据来源: Taylor