Person: Morales González, Domingo
Loading...
First Name
Domingo
Last Name
Morales González
Affiliation
Universidad Complutense de Madrid
Faculty / Institute
Ciencias Matemáticas
Department
Area
Estadística e Investigación Operativa
Identifiers
8 results
Search Results
Now showing 1 - 8 of 8
Item Divergence-based confidence intervals in false-positive misclassification model(Journal of Statistical Computation and Simulation, 2008) Martín Apaolaza, Níriam; Morales González, Domingo; Pardo Llorente, LeandroIn this article, we introduce minimum divergence estimators of parameters of a binary response model when data are subject to false-positive misclassification and obtained using a double-sampling plan. Under this set up, the problem of goodness-of-fit is considered and divergence-based confidence intervals (CIs) for a population proportion parameter are derived. A simulation experiment is carried out to compare the coverage probabilities of the new CIs. An application to real data is also given.Item Rényi statistics for testing composite hypotheses in general exponential models.(Statistics, 2004) Morales González, Domingo; Pardo Llorente, Leandro; Pardo Llorente, María del Carmen; Vadja, IgorWe introduce a family of Renyi statistics of orders r is an element of R for testing composite hypotheses in general exponential models, as alternatives to the previously considered generalized likelihood ratio (GLR) statistic and generalized Wald statistic. If appropriately normalized exponential models converge in a specific sense when the sample size (observation window) tends to infinity, and if the hypothesis is regular, then these statistics are shown to be chi(2)-distributed under the hypothesis. The corresponding Renyi tests are shown to be consistent. The exact sizes and powers of asymptotically alpha-size Renyi, GLR and generalized Wald tests are evaluated for a concrete hypothesis about a bivariate Levy process and moderate observation windows. In this concrete situation the exact sizes of the Renyi test of the order r = 2 practically coincide with those of the GLR and generalized Wald tests but the exact powers of the Renyi test are on average somewhat better.Item Renyi statistics in directed families of exponential experiments(Statistics, 2000) Morales González, Domingo; Pardo Llorente, Leandro; Vadja, IgorRenyi statistics are considered in a directed family of general exponential models. These statistics are defined as Renyi distances between estimated and hypothetical model. An asymptotically quadratic approximation to the Renyi Statistics is established, leading to similar asymptotic distribution results as established in the literature For the likelihood ratio statistics. Some arguments in favour of the Renyi statistics are discussed, and a numerical comparison of the Renyi goodness-of-fit tests with the Likelihood ratio test is presented.Item Approximations to powers of phi-disparity goodness-of-fit tests(Communications in statistics. Theory and methods, 2001) Menéndez Calleja, María Luisa; Morales González, Domingo; Pardo Llorente, Leandro; Vadja, IgorThe paper studies a class of tests based on disparities between the real-valued data and theoretical models resulting either from fixed partitions of the observation space, or from the partitions by the sample quantiles of fixed orders. In both cases there are considered the goodness-of-fit tests of simple and composite hypotheses. All tests are shown to be consistent, and their power is evaluated at the nonlocal as well as local alternatives.Item Limit laws for disparities of spacings(Journal of Nonparametric Statistics, 2003) Morales González, Domingo; Pardo Llorente, Leandro; Pardo Llorente, María del Carmen; Vadja, IgorDisparities of spacings mean the phi-disparities D-phi((q) over bar (n), p(n)) of discrete hypothetical and empirical distributions g and p(n) defined by m-spacings on i.i.d. samples of size n where phi: (0, infinity) \--> HR is twice continuously differentiable in a neighborhood of 1 and strictly convex at 1. It is shown that a slight modification of the disparity statistics introduced for testing the goodness-of-fit in 1986 by Hall are the phi-disparity statistics D-n(phi) = nD(phi) ((q) over bar (n), p(n)). These modified statistics can be ordered for 1 less than or equal to m less than or equal to n as to their sensitivity to alternatives. The limit laws governing for n --> infinity the distributions of the statistics under local alternatives are shown to be unchanged by the modification, which allows to construct the asymptotically a-level goodness-of-fit tests based on D-n(phi). In spite of that the limit laws depend only on the local properties of phi in a neighborhood of 1, we show by a simulation that for small and medium sample sizes n the true test sizes and powers significantly depend on phi and also on the alternatives, so that an adaptation of phi to concrete situations can improve performance of the phi-disparity test. Relations of D-n(phi) to some other m-spacing statistics known from the literature are discussed as well.Item Likelihood divergence statistics for testing hypotheses about multiple population(Communications in Statistics - Simulation and Computation, 2001) Morales González, Domingo; Pardo Llorente, Leandro; Pardo Llorente, María del CarmenThe problem of introducing divergence-based statistics to test composite hypotheses related to s populations is still open when sample sizes are not equal. On the basis of likelihood divergence statistics, a statistical procedure is introduced in this paper and its large sample behaviour is studied. By using Renyi divergence, the proposed statistical procedure is applied to the problem of testing for the homogeneity of several variances. Members of the family of likelihood Renyi divergence statistics are compared for power and checked for fidelity to type I error rates with some classical test statistics. Results of the Monte Carlo simulation study are discussed and presented in tables.Item On efficient estimation in continuous models based on finitely quantized observations(Communications in statistics. Theory and methods, 2006) Morales González, Domingo; Pardo Llorente, Leandro; Vadja, IgorWe consider minimum phi-divergence estimators (theta) over cap (phi)(n) of parameters theta of arbitrary dominated models mu(theta) << lambda on the real line, based on finite quantizations of i.i.d. observations X-1,..., X-n from these models. The quantizations are represented by finite interval partitions P-n = (A(n1),...,A(nmn)) of the real line, where m(n) is allowed to increase to infinity for n --> infinity. The models with densities f(theta) = d mu(theta)/d lambda are assumed to be regular in the sense that they admit finite Fisher informations J(theta). In the first place we have in mind continuous models dominated by the Lebesgue measure lambda. Owing to the quantizations, (theta) over cap (phi)(n) are discrete-model estimators for which the desirable properties ( computation complexity, robustness, etc.) can be controlled by a suitable choice of functions phi. We formulate conditions under which these estimators are consistent and efficient in the original models mu(theta) in the sense that root n((theta) over cap (phi)(n)-theta) -->(L) N(0, J(theta)(-1)) as n --> infinity.Item Two approaches to grouping of data and related disparity statistics(Communications in statistics. Theory and methods, 1988) Menéndez Calleja, María Luisa; Morales González, Domingo; Pardo Llorente, Leandro; Vadja, IgorCsiszar's phi-divergences of discrete distributions are extended to a more general class of disparity measures by restricting the convexity of functions phi(t), t > 0, to the local convexity at t = 1 and monotonicity on intervals (0, 1) and (1, infinity). Goodness-of-fit estimation and testing procedures based on the phi-disparity statistics are introduced. Robustness of the estimation procedure is discussed and the asymptotic distributions for the testing procedure are established in statistical models with data grouped according to their values or orders.