摘要:

Bootstrap methods in curve estimation have been introduced for smoothing parameter selection and for construction of confidence intervals. Most of the papers on confidence intervals use explicit bias estimation or the technique of "undersmoothing" to deal with bias. Coverage accuracy has only been considered for curve estimates with constant variance function. In this paper we show that explicit bias estimation even with heteroscedastic variance structure leads to an improvement of coverage accuracy, when compared to undersmoothing. Bootstrapping with this bias correction using the so-called wild bootstrap leads to an improved coverage accuracy.

ISSN:0233-1888    

DOI:10.1080/02331889508802498

出版商:Gordon & Breach Science Publishers    

年代:1995

数据来源: Taylor

摘要:

An extensive literature has been devoted to the problem of order choice in autoregressive models. Most of alternative methods to hypothesis tests are based on the minimization of the Akaike Information Criterion (AIC) or on some of its variants. These methods have the main drawback to have to assume a parametric form for the autoregression function. The aim of this paper is to present a nonparametric approach that allows to estimate the autoregression order without limiting ourself to any restrictive parametric class of processes. Our technique is in the same spirit as AIC criterion, in the sense that it is based on the minimization of some prediction error. Both theoretical and computational aspects of this method are discussed in this paper.

ISSN:0233-1888    

DOI:10.1080/02331889508802499

出版商:Gordon & Breach Science Publishers    

年代:1995

数据来源: Taylor

摘要:

Letfnbe a histogram estimate constructed from a sample of i.i.d. real-valued random variables with common continuously differentiable densityf. In this paper we prove a central limit theorem for theL1error. We determine a positive constant 0 <σ2≤ 1 − 2/π in order that, under the usual conditions of consistency, the law of be asymptotically Gaussian ,N(0, 1).

ISSN:0233-1888    

DOI:10.1080/02331889508802500

出版商:Gordon & Breach Science Publishers    

年代:1995

数据来源: Taylor

摘要:

Hidden Markov models (HMMs) have during the last decade become a widely spread tool for modelling sequences of dependent random variables. Inference for HMMs has been considered by several authors, but so far no work has been done on estimating their order. In this paper we propose a penalized likelihood estimator for this purpose. This estimator is based on them-dimensional distribution of HMM, and it is shown that in the limit it does not underestimate the order.

ISSN:0233-1888    

DOI:10.1080/02331889508802501

出版商:Gordon & Breach Science Publishers    

年代:1995

数据来源: Taylor

摘要:

In this article we investigate the following problem: Find an appropriate test which based on a spatially restricted observation of a (generalized) germ-grain model allows to decide whether interpretration of the grains of this set is possible or not. For two special hypotheses different test statistics are proposed which are useful under particular interpretations of the problem. Some of their properties are given. A conditional test based on the generalized likelihood ratio principle leads to a very simple determination of the critical values and of the power function.

ISSN:0233-1888    

DOI:10.1080/02331889508802502

出版商:Gordon & Breach Science Publishers    

年代:1995

数据来源: Taylor

摘要:

Algebraic properties of the Hadamard product are used to establish some statistical properties.

ISSN:0233-1888    

DOI:10.1080/02331889508802503

出版商:Gordon & Breach Science Publishers    

年代:1995

数据来源: Taylor

摘要:

Letbe the order statistics of a sample of sizen≥ 2 from a population with continuous distribution functionF. In this paper, we obtain the distribution functionFfrom conditional expectationor. wherehis a real, continuous and strictly monotonic function. We give the necessary and sufficient conditions so that any real function ξ(x) is equal tooris equal to. Different continuous distributions are also characterized using our results.

ISSN:0233-1888    

DOI:10.1080/02331889508802504

出版商:Gordon & Breach Science Publishers    

年代:1995

数据来源: Taylor

ISSN:0233-1888    

DOI:10.1080/02331889508802497

出版商:Gordon & Breach Sceince Publishers    

年代:1995

数据来源: Taylor