JIMÉNEZ GAMERO , María Dolores

This paper studies the problem of simultaneously testing that each of k independent samples come from a normal population. The means and variances of those populations may differ. The proposed procedures are based on the BHEP test and they allow k to increase, which can be even larger than the sample sizes.

LetX1,X2,...be independent and identically distributedrandom elements taking values in a separable HilbertspaceH. With applications for functional data in mind,Hmay be regarded as a space of square-integrable func-tions, defined on a compact interval. We propose andstudy a novel test of the hypothesisH0thatX1has someunspecified nondegenerate...

We generalize a recent class of tests for univariate normality that are based on the empirical moment generating function to the multivariate setting, thus obtaining a class of affine invariant, consistent and easy-to-use goodness-of-fit tests for multinormality. The test statistics are suitably weighted L2-statistics, and we provide their...

Bivariate count data arise in several different disciplines and the bivariate Poisson distribution is commonly used to model them. This paper proposes and studies a computationally convenient goodness-of-fit test for this distribution, which is based on an empirical counterpart of a system of equations. The test is consistent against fixed...

En este trabajo hacemos una extensión de la métrica de Hausdorff H sobre C(Rn), el espacio de todos los conjuntos difusos cerrados en Rn, obteniendo una familia de métricas Df. Estudiamos algunas propiedades topológicas del espacio métrico (C(Rn), Df).

Given k independent samples of functional data, this paper deals with the problem of testing for the equality of their mean functions. In contrast to the classical setting, where k is kept fixed and the sample size from each population increases without bound, here k is assumed to be large and the size of each sample is either bounded or small...

Several procedures have been proposed for testing goodness-of-fit to the error distribution in nonparametric regression models. The null distribution of the associated test statistics is usually approximated by means of a parametric bootstrap which, under certain conditions, provides a consistent estimator. This paper considers a...

Goodness-of-fit tests for the innovation distribution in GARCH models based on measuring deviations between the empirical characteristic function of the residuals and the characteristic function under the null hypothesis have been proposed in the literature. The asymptotic distributions of these test statistics depend on unknown quantities, so...

We provide novel characterizations of multivariate normality that incorporate both the characteristic function and the moment generating function, and we employ these results to construct a class of affine invariant, consistent and easy-to-use goodness-of-fit tests for normality. The test statistics are suitably weighted L2-statistics, and we...

The Muth distribution is a continuous random variable introduced inthe context of reliability theory. In this paper, some mathematical properties of themodel are derived, including analytical expressions for the moment generating func-tion, moments, mode, quantile function and moments of the order statistics. In thisregard, the...

The Muth distribution is a continuous random variable introduced in the context of reliability theory. In this paper, some mathematical properties of the model are derived, including analytical expressions for the moment generating function, moments, mode, quantile function and moments of the order statistics. In this regard, the generalized...

The usefulness of the parameters (e.g., slope, aspect) derived from a Digital Elevation Model (DEM) is limited by its accuracy. In this paper, a thematic-like quality control (class-based) of aspect and slope classes is proposed. A product can be compared against a reference dataset, which provides the quality requirements to be achieved, by...

This paper focuses on the consequences of assuming a wrong model for multinomial data when using minimum penalized φ-divergence, also known as minimum penalized disparity estimators, to estimate the model parameters. These estimators are shown to converge to a well-defined limit. An application of the results obtained shows that a parametric...

Since bootstrap samples are simple random samples with replacement from the original sample, the information content of some bootstrap samples can be very low. To avoid this fact, some authors have proposed several variants of the classical bootstrap. In this paper we consider two of them: the sequential or Poisson bootstrap and the reduced...

In this paper we study a modified bootstrap that consists of only considering those bootstrap samples satisfying k1 ≤ νn ≤ k2, for some 1 ≤ k1 ≤ k2 ≤ n, where νn is the number of distinct original observations in the bootstrap sample. We call it reduced bootstrap, since it only uses a portion of the set of all possible bootstrap samples. We...

We propose a class of goodness–of–fit test procedures for arbitrary parametric families of circular distributions with unknown parameters. The tests make use of the specific form of the characteristic function of the family being tested, and are shown to be consistent. We derive the asymptotic null distribution and suggest that the new method...

In this paper we are interested in checking whether the conditional variances are equal in k ≥ 2 location-scale regression models. Our procedure is fully nonparametric and is based on the comparison of the error distributions under the null hypothesis of equality of variances and without making use of this null hypothesis. We propose four...

In this paper we are interested in checking whether the conditional variances are equal in k ≥ 2 location-scale regression models. Our procedure is fully nonparametric and is based on the comparison of the error distributions under the null hypothesis of equality of variances and without making use of this null hypothesis. We propose four test...

This article studies a new procedure to test for the equality of k regression curves in a fully nonparametric context. The test is based on the comparison of empirical estimators of the characteristic functions of the regression residuals in each population. The asymptotic behaviour of the test statistic is studied in detail. It is shown that...

This article studies a new procedure to test for the equality of k regression curves in a fully non-parametric context. The test is based on the comparison of empirical estimators of the characteristic functions of the regression residuals in each population. The asymptotic behaviour of the test statistic is studied in detail. It is shown that...

En este trabajo se aborda fundamentalmente el estudio de las encuestas que utilizan la herramienta de Internet para su realización. En concreto su objetivo se centra en el planteamiento y desarrollo de diseños muestrales probabilísticos que permitan realizar encuestas desde la World Wide Web con el rigor necesario para poder inferir los...