On Measures of Uniformly Distributed Sequences and Benford's Law.
On Median Unbiased Estimates.
On Minimum Distance Estimators for Unimodel Densities.
On nonparametric estimators of location of maximum
On optimality of the orthogonal block design
In the paper a usual block design with treatment effects fixed and block effects random is considered. To compare experimental design the asymptotic covariance matrix of a robust estimator proposed by Bednarski and Zontek (1996) for simultaneous estimation of shift and scale parameters is used. Asymptotically A- and D- optimal block designs in the class of designs with bounded block sizes are characterized.
On order statistics for random sample size having compound binomial and Poisson distributions
On orthogonal series estimation of bounded regression functions
The problem of nonparametric estimation of a bounded regression function , [a,b] ⊂ ℝ, d ≥ 1, using an orthonormal system of functions , k=1,2,..., is considered in the case when the observations follow the model , i=1,...,n, where and are i.i.d. copies of independent random variables X and η, respectively, the distribution of X has density ϱ, and η has mean zero and finite variance. The estimators are constructed by proper truncation of the function , where the coefficients are determined...
On pointwise adaptive curve estimation based on inhomogeneous data
We want to recover a signal based on noisy inhomogeneous data (the amount of data can vary strongly on the estimation domain). We model the data using nonparametric regression with random design, and we focus on the estimation of the regression at a fixed point x0 with little, or much data. We propose a method which adapts both to the local amount of data (the design density is unknown) and to the local smoothness of the regression function. The procedure consists of a local polynomial...
On power series, Bell polynomials, Hardy-Ramanujan-Rademacher problem and its statistical applications
On robust GMM estimation with applications in economics and finance
Generalized Methods of Moments (GMM) estimators are a popular tool in econometrics since introduced by Hansen (1982), because this approach provides feasible solutions for many problems present in economic data where least squares or maximum likelihood methods fail when naively applied. These problems may arise in errors-in-variable regression, estimation of labor demand curves, and asset pricing in finance, which are discussed here. In this paper we study a GMM estimator for the rank modelingapproach...
On second order efficiency of a robust test and approximations of its error probabilities
On some properties of estimators of a probability density
On some two-step density estimation method.
On Statistical Inference in Concentration Measurement.
On strong laws for generalized L-statistics with dependent data
It is pointed out that a strong law of large numbers for L-statistics established by van Zwet (1980) for i.i.d. sequences, remains valid for stationary ergodic data. When the underlying process is weakly Bernoulli, the result extends even to generalized L-statistics considered in Helmers et al. (1988).
On strong laws of large numbers for arrays of rowwise independent random elements.
On Testing Exponentiality Against IFRA Alternatives.
On Testing for Independence Against Right Tail Increasing in Bivariate Models.
On Testing for Lorenz Ordering.
On testing hypotheses in the generalized Skillings-Mack random blocks setting
The testing of the null hypothesis of no treatment effect against the alternative of increasing treatment effect by means of rank statistics is extended from the classical Friedman random blocks model into an unbalanced design allowing treatments not to be applied simultaneously in each random block. The asymptotic normality of the constructed rank test statistic is proved both in the setting not allowing ties and also for models with presence of ties. As a by-product of the proofs a multiple comparisons...