La généralisation des courbes de fréquence de Pearson par Romanovsky
Large and moderate deviations for Hotelling's -statistic.
Large sample behaviour of the -transformation of two-sample rank statistics
Lattice point problems and the central limit theorem in Euclidean spaces.
Le rôle de la distribution normale en statistique
Limit distribution of the integrated squared error of trigonometric series regression estimator.
Limit distribution of the mean square deviation of the Gasser-Müller nonparametric estimate of the regression function.
Limit distributions of quantiles for a random sample of random length
Limit theorems for bivariate extremes of non-identically distributed random variables
The limit behaviour of the extreme order statistics arising from n two-dimensional independent and non-identically distributed random vectors is investigated. Necessary and sufficient conditions for the weak convergence of the distribution function (d.f.) of the vector of extremes, as well as the form of the limit d.f.'s, are obtained. Moreover, conditions for the components of the vector of extremes to be asymptotically independent are studied.
Limit theorems for rank statistics detecting gradual changes
The purpose of the paper is to investigate weak asymptotic behaviour of rank statistics proposed for detection of gradual changes, linear trends in particular. The considered statistics can be used for various test procedures. The fundaments of the proofs are formed by results of Hušková [4] and Jarušková [5].
Limit theorems for self-normalized large deviation.
Limiting behavior of the perturbed empirical distribution functions evaluated at -statistics for strongly mixing sequences of random variables.
Limiting spectral distribution of circulant type matrices with dependent inputs.
Limiting spectral distribution of XX' matrices
The methods to establish the limiting spectral distribution (LSD) of large dimensional random matrices includes the well-known moment method which invokes the trace formula. Its success has been demonstrated in several types of matrices such as the Wigner matrix and the sample covariance matrix. In a recent article Bryc, Dembo and Jiang [Ann. Probab.34 (2006) 1–38] establish the LSD for random Toeplitz and Hankel matrices using the moment method. They perform the necessary counting of terms in the...
Linear combination, product and ratio of normal and logistic random variables
The distributions of linear combinations, products and ratios of random variables arise in many areas of engineering. In this note, the exact distributions of , and are derived when and are independent normal and logistic random variables. The normal and logistic distributions have been two of the most popular models for measurement errors in engineering.
Linear comparative calibration with correlated measurements
The paper deals with the linear comparative calibration problem, i. e. the situation when both variables are subject to errors. Considered is a quite general model which allows to include possibly correlated data (measurements). From statistical point of view the model could be represented by the linear errors-in-variables (EIV) model. We suggest an iterative algorithm for estimation the parameters of the analysis function (inverse of the calibration line) and we solve the problem of deriving the...
Linear rescaling of the stochastic process
Discussion on the limits in distribution of processes under joint rescaling of space and time is presented in this paper. The results due to Lamperti (1962), Weissman (1975), Hudson Mason (1982) and Laha Rohatgi (1982) are improved here.
Local asymptotic normality for normal inverse gaussian Lévy processes with high-frequency sampling
We prove the local asymptotic normality for the full parameters of the normal inverse Gaussian Lévy process X, when we observe high-frequency data XΔn,X2Δn,...,XnΔn with sampling mesh Δn → 0 and the terminal sampling time nΔn → ∞. The rate of convergence turns out to be (√nΔn, √nΔn, √n, √n) for the dominating parameter (α,β,δ,μ), where α stands for the heaviness of the tails, β the degree of skewness, δ the scale, and μ the location. The essential feature in our study is that the suitably normalized...
Local degeneracy of Markov chain Monte Carlo methods
We study asymptotic behavior of Markov chain Monte Carlo (MCMC) procedures. Sometimes the performances of MCMC procedures are poor and there are great importance for the study of such behavior. In this paper we call degeneracy for a particular type of poor performances. We show some equivalent conditions for degeneracy. As an application, we consider the cumulative probit model. It is well known that the natural data augmentation (DA) procedure does not work well for this model and the so-called...
Loi de Pareto ou loi log-normale : un choix difficile