ISSN:0162-1459    

DOI:10.1080/01621459.1993.10476342

出版商:Taylor & Francis Group    

年代:1993

数据来源: Taylor

ISSN:0162-1459    

DOI:10.1080/01621459.1993.10476343

出版商:Taylor & Francis Group    

年代:1993

数据来源: Taylor

ISSN:0162-1459    

DOI:10.1080/01621459.1993.10476344

出版商:Taylor & Francis Group    

年代:1993

数据来源: Taylor

摘要:

For one-sided tests about the mean of a skewed distribution, thettest is asymptotically robust for validity; however, it can be quite inaccurate and inefficient with small sample sizes. Results presented here confirm that a procedure due to Johnson should be preferred to thettest when the parent distribution is asymmetrical, because it reduces the probability of type I error in cases where thettest has an inflated type I error rate and it is more powerful in other situations. But if the skewness is severe and the sample size is small, then Johnson's test can also be appreciably inaccurate. For such situations, computer-intensive test procedures using bootstrap resampling are proposed, and with an extensive Monte Carlo study it is shown that these procedures are remarkably robust and can result in reduced probabilities of type I and type II errors compared to Johnson's test.

ISSN:0162-1459    

DOI:10.1080/01621459.1993.10476345

出版商:Taylor & Francis Group    

年代:1993

数据来源: Taylor

摘要:

Recurrent event time data are common in medical research; examples include infections in AIDS patients and seizures in epilepsy patients. In this context, as well as in the more usual context of a single failure time variable, time-dependent covariates are frequently of interest. We suggest some rate functions that might be displayed when analyzing recurrent failure time data or when the effect of a categorical time-dependent covariate is of interest. Estimators of these functions are provided along with two-sample test statistics. A new approach to regression modeling of these data is suggested and contrasted with existing methods. Our methods do not require that an explicit model be formulated for the probabilistic association between failure times within an individual. This is in line with the currently popular generalized estimating equation approach to longitudinal data. If the nature of such associations is known or is of particular interest, then alternative methods may be appropriate.

ISSN:0162-1459    

DOI:10.1080/01621459.1993.10476346

出版商:Taylor & Francis Group    

年代:1993

数据来源: Taylor

摘要:

ATS methods provide an approach to fitting curves and surfaces to data using nonparametric regression when distributions are not necessarily Gaussian. First, a small amount of localaveraging(the“A”in ATS) is carried out, then a variance-stabilizingtransformationis applied (“T”), and finally the result issmoothed(“S”) using a nonparametric regression procedure. ATS methods are quite broad in terms of applications; in this article we show how they can be used for fitting a surface when the response is binary, for estimating density, and for estimating the spectrum of a time series. We also present some theoretical investigations that give guidance on how to choose the amount of averaging and how efficient the methods are.

ISSN:0162-1459    

DOI:10.1080/01621459.1993.10476347

出版商:Taylor & Francis Group    

年代:1993

数据来源: Taylor

摘要:

Average derivative functionals of regression are proposed for nonparametric model selection and diagnostics. The functionals are of the integral type, which under certain conditions allows their estimation at the usual parametric rate ofn–1/2. We analyze asymptotic properties of the estimators of these functionals, based on kernel regression. These estimators can then be used for assessing the validity of various restrictions imposed on the form of regression. In particular, we show how they could be used to reduce the dimensionality of the model, assess the relative importance of predictors, measure the extent of nonlinearity and nonadditivity, and, under certain conditions, help identify projection directions in projection pursuit models and decide on the number of these directions.

ISSN:0162-1459    

DOI:10.1080/01621459.1993.10476348

出版商:Taylor & Francis Group    

年代:1993

数据来源: Taylor

摘要:

This article proposes a new data-driven method for selecting the smoothing parameter involved in constructing kernel-based adaptive location estimators. The method consists of minimizing a cross-validatory criterion with respect to the bandwidth occurring in the kernel-type estimators of the efficient score function. It is shown that the location estimator with a data-driven bandwidth selector is indeed an adaptive estimator. A simulation study reveals that the method is also practicable, showing that our estimator performs well in comparison with some other well-known location estimators. It also shows that our method has comparable finite sample performance with the bootstrap method of selecting the smoothing parameter and yet has great computational advantages.

ISSN:0162-1459    

DOI:10.1080/01621459.1993.10476349

出版商:Taylor & Francis Group    

年代:1993

数据来源: Taylor

摘要:

This article discusses a generic feature of density estimation by local smoothing, namely that estimated derivatives and location score vectors will display a systematic downward (attenuation) bias. We study the behavior of kernel estimators, indicating how the derivative bias arises and showing a simple result. We then consider the estimation of score vectors (negative log-density derivatives), which are motivated by the problem of estimating average derivatives and the adaptive estimation of regression models. Using “fixed bandwidth” limits, we show how scores are proportionally downward biased for normal densities and argue from normal mixture densities that proportional bias can be a reasonable approximation. We propose a simple diagnostic statistic for score bias.

ISSN:0162-1459    

DOI:10.1080/01621459.1993.10476350

出版商:Taylor & Francis Group    

年代:1993

数据来源: Taylor

摘要:

This article examines the robustness of the likelihood ratio tests for a change point in simple linear regression. We first summarize the normal theory of Kim and Siegmund, who have considered the likelihood ratio tests for no change in the regression coefficients versus the alternatives with a change in the intercept alone and with a change in the intercept and slope. We then discuss the robustness of these tests. Using the convergence theory of stochastic processes, we show that the test statistics converge to the same limiting distributions regardless of the underlying distribution. We perform simulations to assess the distributional insensitivity of the test statistics to a Weibull, a lognormal, and a contaminated normal distribution in two different cases: fixed and random independent variables. Numerical examples illustrate that the test has a correct size and retains its power when the distribution is nonnormal. We also study the effects of the independent variable's configuration with the aid of a numerical example.

ISSN:0162-1459    

DOI:10.1080/01621459.1993.10476351

出版商:Taylor & Francis Group    

年代:1993

数据来源: Taylor