Showing papers in "Statistics & Probability Letters in 1990"

TL;DR: In this article, an approach towards a random number generator that passes all of the stringent tests for randomness we have put to it, and that is able to produce exactly the same sequence of uniform random variables in a wide variety of computers, including TRS80, Apple, Macintosh, Commodore, Kaypro, IBM PC, AT, PC and AT clones, Sun, Vax, IBM 360 370, 3090, Amdahl, CDC Cyber and even 205 and ETA supercomputers.

TL;DR: A new proof of the almost sure central limit theorem for weakly dependent random variables was given in this paper. But it is based on an almost sure invariance principle and extends to weakly dependent random variables.

TL;DR: In this article, the point process of excess values of peaks above a high level u and demonstrate that this converges in distribution to a Compound Poisson Process as u → ∞ under appropriate assumptions.

TL;DR: In this paper, the problem of estimating the density of U when only independent copies of X = U + Z is observable where Z is an independent measurement error was studied and convergence rates of a family of deconvolved kernel density estimators were obtained under different assumptions on Z.

TL;DR: It is noted that the uniform is the optimal kernel density for kernel estimation of the distribution function, or its inverse, and that several other popular kernel densities perform virtually as well.

TL;DR: In this article, families of min-stable multivariate exponential and multivariate extreme value distributions are presented, and two families have a representation like the Marshall-Olkin multiivariate exponential distribution.

TL;DR: For a sequence of independent Bernoulli trials with probabilities of success and failure p and q respectively, the sooner and later waiting time random variables for the succession quota (s successes and r failures) are studied by deriving a generalized pgf and obtaining the means and variances as discussed by the authors.

TL;DR: In this article, a short proof of the validity and unimodality of Linnik's characteristic function 1/(1 + | t |α), 0 S α V 1 α, where Sα is a symmetric stable random variable with parameter α, and V is an independent exponential random variable.

TL;DR: In this article, the analysis of structural equation models with polytomous variables is discussed and a theory for the full simultaneous maximum likelihood estimation of the thresholds and the covariance structure parameters is developed.

TL;DR: In this paper, large deviation probabilities for two classes of weakly dependent processes, moving averages of i.i.d. random variables and Poisson center cluster random measures are computed.

TL;DR: In this paper, the authors developed a small sample criterion (L1cAIC) for the selection of least absolute deviations regression models, which provides an unbiased estimator for the expected Kullback-Leibler information, assuming that the errors have a double exponential distribution.

TL;DR: In this article, a specific formula is derived for P(N(k)n = x) which is alternative to the one established by Philippou and Makri (1986), and Hirano (1986) and which is in a form suitable for the computation of asymptotic distributions.

TL;DR: Mean squared error properties of kernel estimates of regression quantiles, for both fixed and random design cases, are derived and discussed in this paper, where the authors also consider the effect of random design.

TL;DR: In this paper, the authors presented a variation generation algorithm for lifetimes when survival models incorporate time dependent covariates, which is closed form for special cases of the function that links the covariate values to the survivor distribution.

TL;DR: In this paper, it was shown that applying a very general half-samples approach to the Oja criterion function leads to a class of estimators enjoying the 50% breakdown property and containing, as a special case, Rousseeuw's (1985, 1987) minimum covariance determinant estimator.

TL;DR: In this article, the authors derived a constructive result about the approximation of a Bayes estimator by a mixture of these primitive estimators with respect to a uniform distribution on spheres.

TL;DR: This article gives some connections between this algorithm, known as EMS, and maximizing a penalized likelihood and derives an upper bound on the convergence rate.

TL;DR: In this paper, a recursion technique is used for maximizing the likelihood function and for carrying out the EM algorithm when only noisy data are available, and asymptotic properties are discussed and simulation results are presented.

TL;DR: In this paper, the authors discuss the invariance problem and describe the maximum attainable local power at the origin for unbiased tests, and numerically construct a test with these properties for the problem with two groups.

TL;DR: In this paper, a short proof of a Jensen-type inequality involving the mean and variance of random variables and valid for a class of functions having a convexity-like property is given.

TL;DR: In this article, kernel type estimators of the density of weakly dependent random variables are studied and uniform strong consistency of the estimators and their rates of convergence are obtained, and the dependence condition used is weaker than the strong mixing condition.

TL;DR: In this article, upper bounds for the covariance of the order statistics of a sample of size two from an absolutely continuous random variable X were derived. But they were not used to derive characterizations for specific distributions.

TL;DR: In this paper, the Q-addition of random variables has been shown to be equivalent to dispersive ordering, and a weaker ordering based on the spread function has been proposed.

TL;DR: In this article, the optimal approximation rates of empirical P-P and Q-Q plot processes by sequences of Brownian bridges were established. But the approximation rates were not considered.

TL;DR: In this article, the authors show that the limiting behavior of Dn,r, as n → ∞, is determined by the two-dimensional faces and one-dimensional edges of the boundary of Cd.

TL;DR: In this paper, a simple method for improving Hartley-David-Gumbel's universal bound for the mean of extreme order statistics is presented, which is the same as the one presented in this paper.

TL;DR: In this paper, a class of linear rank statistics is considered for testing a sequence of independent random variables with common distribution against alternatives involving a change in distribution at an unknown time point, and it is shown that under the null hypothesis and suitably normalized, this class of statistics converges in distribution to the double exponential extreme value distribution.

TL;DR: In this paper, one-step deletion diagnostics, influence functions and curvature diagnostics are used to detect influential observations for the Weibull model fit to censored data are discussed.

TL;DR: In this article, it was shown that this strategy of bandwidth selection is not optimal for kernel estimators of an unknown density, and a data-based bandwidth which is as close to the (nonrandom, unknown) minimiser of the Mean Integrated Squared Error as possible was proposed.

TL;DR: In this article, a new variant of a branching process is introduced, with sufficient conditions for it to persist and to die out, and the model is applied to discuss the asymptotic stability of a new type of queuing process.