摘要:

For the regression model in which an explanatory variable contains measurement error, the instrumental variable and the correction for attenuation estimators of slope are considered. Although each requires extra information that is rarely available in ideal form, examinations of asymptotic variances and simulation results suggest that the correction for attenuation performs as well as a fairly strong instrumental variable when the measurement errors are not too large, and this is often true even when the extra information acquired is rough. For larger measurement errors the correction method is of less value. Whenever both kinds of information are available, an estimator with smaller variance is possible by taking a weighted average of the two.

ISSN:0162-1459    

DOI:10.1080/01621459.1986.10478257

出版商:Taylor & Francis Group    

年代:1986

数据来源: Taylor

摘要:

Suppose thaty1, …,ykare normal random variables with ordered meansu1≤u2≤ … ≤uk. A confidence bound is found for eachuithat takes advantage of the ordering. The upper and lower bounds are the maximum and minimum values ofxsuch that the hypotheses thatx<uiandui<xare accepted by their respective likelihood ratio tests. These bounds are often more precise than the usual bounds and can be used to determine the safety of a toxin and to bound the virtual safe dose in a low-dose extrapolation. Simultaneous intervals foru1, …,ukare also derived.

ISSN:0162-1459    

DOI:10.1080/01621459.1986.10478258

出版商:Taylor & Francis Group    

年代:1986

数据来源: Taylor

摘要:

A prediction density functiong* for the normal linear model is derived. This function is shown to dominate three well-known prediction densities by first constructing a specified class of densities that includes these three and then proving thatg* is the optimal member of this class in the sense of minimizing a criterion based on the Kullback—Leibler divergence.g* coincides with a Bayesian prediction density assuming diffuse prior.

ISSN:0162-1459    

DOI:10.1080/01621459.1986.10478259

出版商:Taylor & Francis Group    

年代:1986

数据来源: Taylor

摘要:

A sequence of independent multivariate normal vectors with equal but possibly unknown variance matrices are hypothesized to have equal mean vectors, and we wish to test that the mean vectors have changed after an unknown point in the sequence. The likelihood ratio test is based on the maximum HotellingT2for the sequences before and after the change point. The main result is a conservative approximation for its null distribution based on an improved Bonferroni inequality. If the change is judged significant, then further changes are estimated by splitting the two subsequences formed by the first change point. The methods can also be used to test for a change in row probabilities of a contingency table, allowing for extramultinomial variation. The results are used to find changes in a set of geological data previously analyzed by Chernoff (1973) by the “faces” method and to find changes in the frequencies of pronouns in the plays of Shakespeare.

ISSN:0162-1459    

DOI:10.1080/01621459.1986.10478260

出版商:Taylor & Francis Group    

年代:1986

数据来源: Taylor

摘要:

The problem of estimating the mean of an exponential distribution is studied, when the data available are a random sample of time-censoredrth-order statistics. Examples for such empirical situations are cited. Maximum likelihood estimators (MLE's) and moment-equation estimators (MEE's) are studied. Theoretical derivations are provided for the large sample variances and distributions of these estimators. The efficiency of the MEE compared to the MLE is studied.

ISSN:0162-1459    

DOI:10.1080/01621459.1986.10478261

出版商:Taylor & Francis Group    

年代:1986

数据来源: Taylor

摘要:

This article gives necessary and sufficient conditions for the equivalence of the simple linear unbiased estimator (SLUE) and the best linear unbiased estimator (BLUE) of the parameters when there arekindependent sources of Type II censored data from a location scale distribution in which the location parameter is an unknown linear function of certain given independent variables and the scale parameter is an unknown constant. It also shows that the BLUE can be obtained in a two-stage procedure that has the same model-checking features and computational simplicity of the SLUE.

ISSN:0162-1459    

DOI:10.1080/01621459.1986.10478262

出版商:Taylor & Francis Group    

年代:1986

数据来源: Taylor

ISSN:0162-1459    

DOI:10.1080/01621459.1986.10478263

出版商:Taylor & Francis Group    

年代:1986

数据来源: Taylor

摘要:

The Hellinger distance between a nonparametric density estimator and a model family is minimized to produce estimates of location and covariance in multivariate data. With suitable restrictions on the density estimators and the model family, these minimum Hellinger distance estimators (MHDE's) are shown to be affine invariant, consistent, and asymptotically normal. The robustness of the MHDE as measured by the breakdown point compares favorably against the previously studiedM-estimators. Monte Carlo results suggest that the MHDE's are an attractive robust alternative to the usual sample means and covariance matrix.

ISSN:0162-1459    

DOI:10.1080/01621459.1986.10478264

出版商:Taylor & Francis Group    

年代:1986

数据来源: Taylor

摘要:

We show that Kronmal and Tarter's well-known rule for selecting the terms in an orthogonal series density estimator can lead to poor performance and even inconsistency in certain cases. These difficulties arise when the underlying density has a nonmonotone sequence of Fourier coefficients, as is likely to be the case with sharply peaked or multimodal distributions. We suggest a way of overcoming these shortcomings.

ISSN:0162-1459    

DOI:10.1080/01621459.1986.10478265

出版商:Taylor & Francis Group    

年代:1986

数据来源: Taylor

ISSN:0162-1459    

DOI:10.1080/01621459.1986.10478266

出版商:Taylor & Francis Group    

年代:1986

数据来源: Taylor