Characterizations of a mixture of two general distributions
Comparing algorithms based on marginal problem
The paper deals with practical aspects of decision making under uncertainty on finite sets. The model is based on marginal problem. Numerical behaviour of 10 different algorithms is compared in form of a study case on the data from the field of rheumatology. (Five of the algorithms types were suggested by A. Perez.) The algorithms (expert systems, inference engines) are studied in different situations (combinations of parameters).
Comparing estimation methods for the FPLD.
Components of goodness-of-fit statistics
Compound Gamma Bivariate Distributions.
Computing the distribution of a linear combination of inverted gamma variables
A formula for evaluation of the distribution of a linear combination of independent inverted gamma random variables by one-dimensional numerical integration is presented. The formula is direct application of the inversion formula given by Gil–Pelaez [gil-pelaez]. This method is applied to computation of the generalized -values used for exact significance testing and interval estimation of the parameter of interest in the Behrens–Fisher problem and for variance components in balanced mixed linear...
Conditions nécessaires et suffisantes de convergence L1 en probabilité de l'histogramme pour une densité
Constructing median-unbiased estimators in one-parameter families of distributions via stochastic ordering
If θ ∈ Θ is an unknown real parameter of a given distribution, we are interested in constructing an exactly median-unbiased estimator θ̂ of θ, i.e. an estimator θ̂ such that a median Med(θ̂ ) of the estimator equals θ, uniformly over θ ∈ Θ. We shall consider the problem in the case of a fixed sample size n (nonasymptotic approach).
Construction of multivariate distributions: a review of some recent results.
The construction of multivariate distributions is an active field of research in theoretical and applied statistics. In this paper some recent developments in this field are reviewed. Specifically, we study and review the following set of methods: (a) Construction of multivariate distributions based on order statistics, (b) Methods based on mixtures, (c) Conditionally specified distributions, (d) Multivariate skew distributions, (e) Distributions based on the method of the variables in common and...
Coodness of fit test Statistics based on Riedwyl-type derivations
Core functions and core divergences of regular distributions
On bounded or unbounded intervals of the real line, we introduce classes of regular statistical families, called Johnson families because they are obtained using generalized Johnson transforms. We study in a rigorous manner the formerly introduced concept of core function of a distribution from a Johnson family, which is a modification of the well known score function and which in a one-to-one manner represents the distribution. Further, we study Johnson parametrized families obtained by Johnson...
Correlation analysis: Exact permutation paradigm