Showing papers in "Journal of Statistical Planning and Inference in 2002"

TL;DR: The perception-based theory of probabilistic reasoning which is outlined in this paper is not in the traditional spirit, but its principal aim is to lay the groundwork for a radical enlargement of the role of natural languages in probability theory and its applications, especially in the realm of decision analysis.

TL;DR: In this paper, the authors consider the application of Bernstein polynomials for approximating a bounded and continuous function and show that it can be naturally adapted for smooth estimation of a distribution function concentrated on the interval [0, 1] by a continuous approximation of the empirical distribution function.

TL;DR: In this article, the authors considered multistage ranked set sampling as a generalization of ranking set sampling, that results in an increase of the efficiency for fixed value of m. This technique is useful when visual ordering of a small set of size can be done easily and fairly accurately, but exact measurement of an observation is difficult and expensive.

TL;DR: In this article, the authors considered three parameter generalized exponential distribution and derived exact expressions for single and product moments of record statistics in terms of Riemann zeta and polygamma functions.

TL;DR: In this paper, an optional randomized response model is proposed for quantifying the sensitivity levels of questions in personal interview surveys and an estimator for the sensitivity level of a question is proposed and an empirical study is carried out to show the validity of the proposed estimation technique.

TL;DR: This paper proposes a new method of classification which involves extending the naive Bayes classifier to credal sets, based on more realistic assumptions and in the direction of more reliable inferences.

TL;DR: In this paper, the AR(∞)-sieve bootstrap procedure is used to construct nonparametric prediction intervals for a general class of linear processes. But the residual resampling from an autoregressive approximation to the given process is not considered.

TL;DR: In this article, the authors consider the least-squares approach for estimating parameters of a spatial variogram and establish consistency and asymptotic normality of these estimators under general conditions.

TL;DR: In this article, a nonparametric bootstrap procedure is proposed for stochastic processes which follow a general autoregressive structure, and the procedure generates bootstrap replicates by locally resampling the original set of observations reproducing automatically its dependence properties.

TL;DR: A central limit theorem for intrinsic mean on a complete flat manifold and some asymptotic properties of the intrinsic total sample variance on an arbitrary complete manifold are given in this paper.

TL;DR: In this paper, a multivariate relative treatment effect is defined which can be estimated by using the mid-ranks of the observations within each component and derive the asymptotic distribution of this estimator.

TL;DR: In this paper, a new closure operation on natural numbers involving candelabra systems was introduced, which makes it possible to generalize various constructions for Steiner 3-designs and to create new infinite families of Steiner 2-and 3-constructions.

TL;DR: In this article, generalized theorems on the optimality of supersaturated designs in terms of low dependency over all pairs of column vectors are presented, and some mixed-level supersaturated design are constructed using a method based on these theorem.

TL;DR: In this article, an entropy characterization of the inverse Gaussian family is presented and used to construct a goodness-of-fit test for ascertaining appropriateness of such models.

TL;DR: In this article, the authors considered two-phase random design linear regression models with arbitrary error densities and where the regression function has a /xed jump at the true change point.

TL;DR: In this paper, the authors survey ways of taking order restrictions into account in the analysis of contingency tables and discuss methods for contingency tables with two rows or two columns that result from comparing several binomial parameters or two multinomial distributions.

TL;DR: In this article, a combinatorial proof of a three term recurrence for the nth Narayana polynomial is given for the Schroder numbers and the Kirkman numbers.

TL;DR: In this article, a new residual-based test for heteroscedasticity in nonparametric regression is proposed, which is motivated by the idea that the problem of testing heterogeneity is equivalent to testing pseudoresiduals for a constant mean.

TL;DR: In this article, a hierarchical time series model is considered to combine information from three relevant sources: (a) Current Population Survey (CPS), (b) Decennial Censuses and (c) Bureau of Economic Analysis.

TL;DR: This paper exploits the explicitness of penalized spline additive models to derive some useful and revealing theoretical approximations.

TL;DR: An exact, no-assumptions approach to dealing with incomplete sets of multivariate categorical data is proposed, and it is shown that the computation of bounds on the expectation of real-valued functions under such distributions is both possible and efficient, by means of linear programming.

TL;DR: Two methods are presented for the aggregation of imprecise probabilities elicited from a group of experts in terms of betting rates, in which the fundamental concept of probability is an interpersonal one, with irreducible game-theoretic elements.

TL;DR: In this paper, the authors present a unified treatment of different types of one-step M-estimation in regression models which incorporates the Newton-Raphson, method of scoring and iteratively reweighted least squares forms of one step estimator.

TL;DR: In this paper, the authors studied the problem of design and analysis of two-period repeated measurements (crossover or changeover) designs based on two or more treatments and showed that if the study is properly designed, one can efficiently estimate any contrast in direct treatment effects even if there are self and simple mixed carryover effects in the data.

TL;DR: In this article, two principal tools, namely the likelihood and the union-intersection principles, are critically appraised with respect to their roles in drawing statistical inference when the parameters are subject to inequality constraints.

TL;DR: In this article, the authors consider the analysis of multivariate longitudinal data assuming a scale multiple of Kronecker product correlation structure for the covariance matrix of the observations on each subject and show that the estimating equations for the correlation parameters in the quasi-least squares method are optimal unbiased estimating equations if the data is from a normal population.

TL;DR: In this paper, the authors proposed a new method called maximum composite likelihood (MCL) for the estimation of variance and covariance components, which is as general applicable as the method of maximum likelihood, but does not require inversion of matrices.

TL;DR: The authors showed that the least square estimator of the finite-dimensional regression coefficient is root-n consistent and asymptotically normal, and that the isotonic estimator has the same limiting distribution in nonparametric monotone density estimation and isotonic regression derived by Prakasa Rao and Brunk.

TL;DR: It is shown that the independent Metropolis-Hastings chain has certain stochastic monotonicity properties that enable a perfect sampling algorithm to be implemented, at least when the candidate is overdispersed with respect to the target distribution.