1,721,051 research outputs found
Consistent tests for symmetric stability with finite mean based on the empirical characteristic function
No full textIn this paper we study a class of goodness-of-fit tests for the symmetric stable distribution. The proposed tests are based on a weighted integral involving the empirical characteristic function, corresponding to suitably centered data. The consistency of the tests is investigated under a moment assumption. Also, as the decay of the weight function tends to infinity, limit statistics are obtained. Our method is applied on real and simulated data. © 2003 Elsevier B.V. All rights reserved
A Class of Omnibus Tests for the Laplace Distribution Based on the Empirical Characteristic Function
No full textIn this paper a class of goodness-of-fit tests for the Laplace distribution is proposed. The tests are based on a weighted integral involving the empirical characteristic function. The consistency of the tests as well as their asymptotic distribution under the null hypothesis are investigated. As the decay of the weight function tends to infinity the test statistics approach limit values. In a particular case the resulting limit statistic is related to the first nonzero component of Neyman's smooth test for this distribution. The new tests are compared with other omnibus tests for the Laplace distribution
A Kolmogorov-Smirnov type test for skew normal distributions based on the empirical moment generating function
No full textIn this paper tests of hypothesis are constructed for the family of skew normal distributions. The proposed tests utilize the fact that the moment generating function of the skew normal variable satisfies a simple differential equation. The empirical counterpart of this equation, involving the empirical moment generating function, yields simple consistent test statistics. Finite-sample results as well as results from real data are provided for the proposed procedures. © 2007 Elsevier B.V. All rights reserved
A new goodness-of-fit test for certain bivariate distributions applicable to traffic accidents
No full textT. Cacoullos and H. Papageorgiou [On some bivariate probability models applicable to traffic accidents and fatalities, Int. Stat. Rev. 48 (1980) 345-356] studied a special class of bivariate discrete distributions appropriate for modeling traffic accidents, and fatalities resulting therefrom. The corresponding random variable may be written as Z = (N, Y)′, with Y = ∑j = 1N Xj, where {Xj}j = 1N, are independent copies of a (discrete) random variable X, and N is independent of {Xj}j = 1N, and follows a Poisson law. If X follows a Poisson law (resp. Binomial law), the resulting distribution is termed Poisson-Poisson (resp. Poisson-Binomial). L2-type goodness-of-fit statistics are constructed for the 'general distribution' of this kind, where X may be an arbitrary discrete nonnegative random variable. The test statistics utilize a simple characterization involving the corresponding probability generating function, and are shown to be consistent. The proposed procedures are shown to perform satisfactorily in simulated data, while their application to accident data leads to positive conclusions regarding the modeling ability of this class of bivariate distributions. © 2006 Elsevier B.V. All rights reserved
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Permutation tests for homogeneity based on the empirical characteristic function
No full textIn this paper, omnibus tests are proposed for testing the homogeneity of two populations. The tests are based on weighted integrals involving the empirical characteristic function. The consistency of the tests as well as their asymptotic distribution under the null hypothesis are investigated. As the decay of the weight functions tends to infinity, the test statistics approach limit values which are related to moment differences between the two populations. The test procedure is based on resampling from the permutation distribution of the test statistic. The new tests are compared with other omnibus tests for homogeneity via a Monte Carlo procedure. © 2005 Taylor & Francis Group Ltd
Testing skew normality via the moment generating function
No full textIn this paper, goodness-of-fit tests are constructed for the skew normal law. The proposed tests utilize the fact that the moment generating function of the skew normal variable satisfies a simple differential equation. The empirical counterpart of this equation, involving the empiricalmoment generating function, yields appropriate test statistics. The consistency of the tests is investigated under general assumptions, and the finite-sample behavior of the proposed method is investigated via a parametric bootstrap procedure. © 2010 Allerton Press, Inc
A unified approach of testing for discrete and continuous Pareto laws
No full textNew tests are proposed for the Pareto distribution as well as its discrete version, the so called Zipf's law. In both cases the discrepancy between the empirical moment of arbitrary negative order and its theoretical counterpart is utilized in a weighted integral test statistic. If the weight function is of exponential rate of decay interesting limit statistics are obtained. The tests are shown to be consistent under fixed alternatives and a Monte Carlo study is drawn to investigate the performance of the proposed procedures in small samples. Furthermore a bootstrap procedure is proposed to cope with the case of unknown shape parameter. We conclude with applications to real data. © 2007 Springer-Verlag
New inference procedures for generalized Poisson distributions
No full textA common feature for compound Poisson and Katz distributions is that both families may be viewed as generalizations of the Poisson law. In this paper, we present a unified approach in testing the fit to any distribution belonging to either of these families. The test involves the probability generating function, and it is shown to be consistent under general alternatives. The asymptotic null distribution of the test statistic is obtained, and an effective bootstrap procedure is employed in order to investigate the performance of the proposed test with real and simulated data. Comparisons with classical methods based on the empirical distribution function are also included
- …
