Asymptotic optimality of new adaptive test in regression model
Asymptotic properties of some tests under almost regular assumptions
Asymptotically Optimal Nonparametric One- and Two-Way Analysis of Variance Tests for the Log Linear Model Under Censoring.
Asymptotics for robust MOSUM
Behaviour of sign test and one sample median test against changes in the model
Block Rank Statistics.
Bootstraping of M-smoothers
Change Point Tests Based on U-Statistics with Applications in Reliability.
Change-point problems: A Bayesian nonparametric approach
A change-point problem is examined from a Bayesian viewpoint, under nonparametric hypotheses. A Ferguson-Dirichlet prior is chosen and the posterior distribution is computed for the change-point and for the unknown distribution functions.
Chi-squared goodness-of-fit test for the family of logistic distributions
Choosing the best -divergence goodness-of-fit statistic in multinomial sampling with linear constraints
In this paper we present a simulation study to analyze the behavior of the -divergence test statistics in the problem of goodness-of-fit for loglinear models with linear constraints and multinomial sampling. We pay special attention to the Rényi’s and -divergence measures.
Classical and bayesian approaches to the change-point problem : fixed sample and sequential procedures
Components of goodness-of-fit statistics
Components of Pearson's statistic for at least partially ordered m-way contingency tables.
Components of the Pearson-Fisher chi-squared statistic.
Concept of Data Depth and Its Applications
Data depth is an important concept of nonparametric approach to multivariate data analysis. The main aim of the paper is to review possible applications of the data depth, including outlier detection, robust and affine-equivariant estimates of location, rank tests for multivariate scale difference, control charts for multivariate processes, and depth-based classifiers solving discrimination problem.
Consistency of a Nonparametric Estimation of a Density Functional.
Construction of Minimax-Tests for Bounded Families of Probability-Densities.
Coodness of fit test Statistics based on Riedwyl-type derivations
Data compression in discriminating stochastic processes