An Extension of the Damage Model.
An Extremal Quotient Test for Exponential Distributions.
An extreme Markovian-evolutionary (EME) sequence.
The most general sequence, with Gumbel margins, generated by maxima procedures in an auto-regressive way (one step) is defined constructively and its properties obtained; some remarks for statistical estimation are presented.
An Identity Concerning a Wishart Matrix.
An Identity for Expectations of Functions of Order Statistics.
An Identity for the Product Moments of Order Statistics.
An Illustration of Harmonic Regression Based on the Results of the Fast Fourier Transformation
An improper Cramer-Rao lower bound
An improved Bayes empirical Bayes estimator.
An index of diversity in stratified random sampling based on the hypoentropy measure.
We consider a measure of the diversity of a population based on the λ-measure of hypoentropy introduced by Ferreri (1980). Our purpose is to study its asymptotic distribution in a stratified sampling and its application to testing hypothesis. A numerical example based on real data is given.
An inductive derivation of Stirling numbers of the second kind and their applications in statistics.
An integral representation for the Hellinger distance.
An integrated selection formulation for the best normal mean: The unequal and unknown variance case.
An interpolation problem for multivariate stationary sequences
Let and be stationarily cross-correlated multivariate stationary sequences. Assume that all values of and all but one values of are known. We determine the best linear interpolation of the unknown value on the basis of the known values and derive a formula for the interpolation error matrix. Our assertions generalize a result of Budinský [1].
An introduction to optimal designs.
An Invariance Principle for Progressively Truncated Likelihood Ratio Statistics.
An Invariance Principle for Reduced U-Statistics.
An Invariance Principle for U-Statistics in Simple Random Sampling without Replacement.
An investigation of chaos in the -diode circuit using the BDS test.
An iterative implementation of the implicit nonlinear filter
Implicit sampling is a sampling scheme for particle filters, designed to move particles one-by-one so that they remain in high-probability domains. We present a new derivation of implicit sampling, as well as a new iteration method for solving the resulting algebraic equations.