摘要:

Within the Neyman-Pearson framework of hypothesis testing with fixed-error-level specifications, two-stage designs are obtained such that sample size is minimized when the alternative hypothesis is true. Normally distributed variates with known variance and binomially distributed variates are considered. It is shown that when the alternative hypothesis is true, these optimal two-stage designs generally achieve between one-half and two-thirds of the ASN differential between the two extremes of analogous fixed-sample designs (maximum ASN) and item-by-item Wald SPRT design (minimum ASN when alternative hypothesis is true).

ISSN:0162-1459    

DOI:10.1080/01621459.1976.10481481

出版商:Taylor & Francis Group    

年代:1976

数据来源: Taylor

摘要:

This study considers the selection of the best few ofafinite population of varieties whose unknown true yields are normally distributed. The selection scheme consists of a series of yield trials each utilizing a specified proportion of the fixed total resources. At each stage certain varieties are rejected; the rest are passed on to the next stage. Increased yields are found to result when rejection is based on information from all previous stages and on external cut-off points rather than a variety's relative position within a cohort.

ISSN:0162-1459    

DOI:10.1080/01621459.1976.10481482

出版商:Taylor & Francis Group    

年代:1976

数据来源: Taylor

摘要:

A general computer program for univariate and multivariate nonorthogonal analysis of variance is described. Its use is illustrated with a two-factor problem with missing cells. It is pointed out that the criticisms of Francis regarding this program are unwarranted.

ISSN:0162-1459    

DOI:10.1080/01621459.1976.10481483

出版商:Taylor & Francis Group    

年代:1976

数据来源: Taylor

摘要:

The power of Durbin'sh-test for autocorrelated error terms is compared with the power of the Durbin-Watsond-test. It is argued that, contrary to conclusions reached elsewhere (see [6]), thed-test outperforms theh-test.

ISSN:0162-1459    

DOI:10.1080/01621459.1976.10481484

出版商:Taylor & Francis Group    

年代:1976

数据来源: Taylor

ISSN:0162-1459    

DOI:10.1080/01621459.1976.10481485

出版商:Taylor & Francis Group    

年代:1976

数据来源: Taylor

摘要:

Statistical inference is examined for the location-scale model, using nonnormal distributions for the error. The development emphasizes necessary analysis that follows as a logical consequence from the data and model alone; only the terminal parts of the analysis use the conventional criteria of estimation and testing. Inferences are obtained concerning the shape of the distribution and concerning the location and scale parameters. Illustrations are included using real and computer-generated data. The more general linear model is examined briefly. The methods extend to the case where the error distribution is unknown in the nonparametric sense; they provide a new and flexible approach to adaptive inference.

ISSN:0162-1459    

DOI:10.1080/01621459.1976.10481486

出版商:Taylor & Francis Group    

年代:1976

数据来源: Taylor

ISSN:0162-1459    

DOI:10.1080/01621459.1976.10481487

出版商:Taylor & Francis Group    

年代:1976

数据来源: Taylor

ISSN:0162-1459    

DOI:10.1080/01621459.1976.10481488

出版商:Taylor & Francis Group    

年代:1976

数据来源: Taylor

ISSN:0162-1459    

DOI:10.1080/01621459.1976.10481489

出版商:Taylor & Francis Group    

年代:1976

数据来源: Taylor

ISSN:0162-1459    

DOI:10.1080/01621459.1976.10481490

出版商:Taylor & Francis Group    

年代:1976

数据来源: Taylor