Application of the selection procedure R to unequal observation numbers
Applying Coefficients of Preference in Ranking (CPR)
Approximate bias for first-order autoregressive model with uniform innovations. Small sample case
The first-order autoregressive model with uniform innovations is considered. The approximate bias of the maximum likelihood estimator (MLE) of the parameter is obtained. Also, a formula for the approximate bias is given when a single outlier occurs at a specified time with a known amplitude. Simulation procedures confirm that our formulas are suitable. A small sample case is considered only.
Approximate construction of a two-dimensional confidence region
Approximated maximum likelihood estimation of parameters of discrete stable family
In this article we propose a method of parameters estimation for the class of discrete stable laws. Discrete stable distributions form a discrete analogy to classical stable distributions and share many interesting properties with them such as heavy tails and skewness. Similarly as stable laws discrete stable distributions are defined through characteristic function and do not posses a probability mass function in closed form. This inhibits the use of classical estimation methods such as maximum...
Approximations and Time-Discretization in Testing One-Sided Hypotheses for the Mean of a Gaussian Process.
Approximations for Markov decision problems
Approximative solutions of stochastic optimization problems
The aim of this paper is to present some ideas how to relax the notion of the optimal solution of the stochastic optimization problem. In the deterministic case, -minimal solutions and level-minimal solutions are considered as desired relaxations. We call them approximative solutions and we introduce some possibilities how to combine them with randomness. Relations among random versions of approximative solutions and their consistency are presented in this paper. No measurability is assumed, therefore,...
Are Robust Estimation Methods Useful in the Structural Errors-in-Variables Model?.
Aspects of control for the normal Markov processes.
Assessing influence in survival data with a cured fraction and covariates.
Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as departures from error assumptions and the presence of outliers and influential observations with the fitted models. Assuming censored data, we considered a classical analysis and Bayesian analysis assuming no informative priors for the parameters of the model with a cure fraction. A Bayesian approach was considered by using Markov Chain Monte Carlo Methods with Metropolis-Hasting algorithms steps to...
Asymptotic analysis for bifurcating autoregressive processes via a martingale approach.
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 approximations to the Bayes posterior risk.
Asymptotic behavior of the likelihood function of covariance matrices of spatial Gaussian processes.
Asymptotic behaviour of a BIPF algorithm with an improper target
The BIPF algorithm is a Markovian algorithm with the purpose of simulating certain probability distributions supported by contingency tables belonging to hierarchical log-linear models. The updating steps of the algorithm depend only on the required expected marginal tables over the maximal terms of the hierarchical model. Usually these tables are marginals of a positive joint table, in which case it is well known that the algorithm is a blocking Gibbs Sampler. But the algorithm makes sense even...
Asymptotic behaviour of an estimator based on Rao's divergence
Asymptotic behaviour of the likelihood ratio test under presence of deviations of the model
Asymptotic behaviour of the robust test in the Rieder's model of contamination
Asymptotic comparison of maximum likelihood and a rank estimate in simple linear regression model