摘要:

We consider univariate regression estimation from an individual (non-random) sequence, which is stable in the sense that for each interval(i) the limiting relative frequency ofAunderx1,x2,… is governed by an unknown probability distributionμ, and (ii) the limiting average of thoseyiwithx∈Ais governed by an unknown regression functionm(·).

ISSN:0233-1888    

DOI:10.1080/02331889908802686

出版商:Gordon & Breach Science Publishers    

年代:1999

数据来源: Taylor

摘要:

A common difficulty when using binomial or Poisson models is that the variance estimates based on the mean/variance structures of these models are often untrustworthy due to overdispersion. One way in which this overdispersion may appear is through unobserved intra-cluster correlation. The normal distribution, as well as many other distributions that allow separate estimation of their mean and variance, are usually regarded as not being affected by overdispersion. This paper shows that the effect of unobserved intra-cluster correlation in the standard normal model is exactly the same as in the binomial or Poisson models. Approaches to detect this type of correlation are also given.

ISSN:0233-1888    

DOI:10.1080/02331889908802687

出版商:Gordon & Breach Science Publishers    

年代:1999

数据来源: Taylor

摘要:

To estimate the densityfof the mean measure of a discrete random measureη, the sequence of the observed random measures is usually supposed to be independent. In this paper, that sequence is associated: this definition is a particular case of association of probability measure on a partially ordered Polish space (Lindqvist [18]). The kernel estimator offconverges in probability and almost surely, pointwise and uniformly, under second-order moment conditions onηnand on the sequence (hn) of the window-widths of the estimator.

ISSN:0233-1888    

DOI:10.1080/02331889908802688

出版商:Gordon & Breach Science Publishers    

年代:1999

数据来源: Taylor

摘要:

Several strong limit theorems are proved for sums of logarithms ofmth order spacings from general distributions. In all given results, the ordermof the spacings is allowed to increase to infinity with the sample size. These results provide a nonparametric strongly consistent estimator of entropy as well as a characterization of the uniform distribution on [0,1]. Furthermore, it is shown that Cressie's (1976) goodness of fit test is strongly consistent against all continuous alternatives.

ISSN:0233-1888    

DOI:10.1080/02331889908802689

出版商:Gordon & Breach Science Publishers    

年代:1999

数据来源: Taylor

摘要:

We establish pointwise and uniform large deviations limit theorems of Chernoff-type for the conditional empirical process. On the other hand, we state the pointwise large deviations theorem for the Nadaraya-Watson estimator of the regression function. The estimations are based on sequences of independent and identically distributed random vectors. We derive then some implications of our results in the study of asymptotic efficiency of goodness-of-fit test based on uniform deviation of the conditional empirical distribution function with respect to its theoretical distribution. Moreover, we deduce the inaccuracy rate in conditional distribution functions estimation.

ISSN:0233-1888    

DOI:10.1080/02331889908802690

出版商:Gordon & Breach Science Publishers    

年代:1999

数据来源: Taylor

ISSN:0233-1888    

DOI:10.1080/02331889908802685

出版商:Gordon & Breach Sceince Publishers    

年代:1999

数据来源: Taylor