A summary on entropy statistics
A Test of Goodness-of-Fit Based on Extreme Spacings with some Efficiency Comparisons.
A weak law of large numbers for the sample covariance matrix.
ABSTRACT - Procedures for Epidemic Alternatives.
Additions and correction to “The bootstrap of the mean with arbitrary bootstrap sample”
Alternative parametric estimation in the exponential case under random censorship
An Approximation to the Limit Distribution of the Epps-Pulley Test Statistic for Normality.
An asymptotic representation of the likelihood ratio for irregular families of distributions in the multivariate case.
An Elementary Method for the Statistical Analysis of Growth Curves.
An extension of Billingsley’s uniform boundedness theorem to higher-dimensional -processes
An Invariance Principle for U-Statistics in Simple Random Sampling without Replacement.
An Outlier Test for Linear Processes.
An Outlier Test for Linear Processes - II. Large Contamination.
Analytic and Asymptotic Properties of Non-Symmetric Linnik's Probability Densities.
Another look at the moment method for large dimensional random matrices.
Approximate Distributions of the Maximum Deviation of Histograms.
Approximation by Poisson law
We present here the results of the investigation on approximation by the Poisson law of distributions of sums of random variables in the scheme of series. We give the results pertaining to the behaviour of large deviation probabilities and asymptotic expansions, to the method of cumulants, with the aid of which our results have been obtained.
Approximation of finite-dimensional distributions for integrals driven by α-stable Lévy motion
We present a method of numerical approximation for stochastic integrals involving α-stable Lévy motion as an integrator. Constructions of approximate sums are based on the Poissonian series representation of such random measures. The main result gives an estimate of the rate of convergence of finite-dimensional distributions of finite sums approximating such stochastic integrals. Stochastic integrals driven by such measures are of interest in constructions of models for various problems arising...
Asymptotic analysis of minimum volume confidence regions for location-scale families
An asymptotic analysis, when the sample size n tends to infinity, of the optimal confidence region established in Czarnowska and Nagaev (2001) is considered. As a result, two confidence regions, both close to the optimal one when n is sufficiently large, are suggested with a mild assumption on the distribution of a location-scale family.
Asymptotic behaviour of empirical multiinformation