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作者：CHAN, KS
摘要：It is shown that, under some regularity conditions, the least squares estimator of a stationary ergodic threshold autoregressive model is strongly consistent. The limiting distribution of the least squares estimator is derived. It is shown that the estimator of the threshold parameter is N consistent and its limiting distribution is related to a compound Poisson process.
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作者：LO, AY
摘要：Bayesian statistical inference for sampling from weighted distribution models is studied. Small-sample Bayesian bootstrap clone (BBC) approximations to the posterior distribution are discussed. A second-order ProPertY for the BBC in unweighted i.i.d. sampling is given. A consequence is that BBC approximations to a posterior distribution of the mean and to the sampling distribution of the sample average, can be made asymptotically accurate by a proper choice of the random variables that generat...
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作者：MESSIG, MA; STRAWDERMAN, WE
作者单位：Rutgers University System; Rutgers University New Brunswick
摘要：Minimal sufficiency and completeness are examined for the multistage, multihit and Weibull quantal response models. It is shown that the response counts are minimal sufficient statistics and conditions are presented for completeness for the families of these models. These results provide an example of a complete sufficient statistic for a curved exponential family which is of higher dimension than the parameter space. Uniformly minimum variance unbiased (UMVU) estimators may not exist for the ...
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作者：PFANZAGL, J
摘要：Let (P(theta,eta):(theta,eta) is-an-element-of THETA x H), with THETA is-an-element-of R and H arbitrary, be a family of mutually absolutely continuous probability measures on a measurable space (X,A). The problem is to estimate theta, based on a sample (x1,...,x(n)) from X1(n)P(theta,etanu). If (eta1,...,eta(n)) are independently distributed according to some unknown prior distribution GAMMA, then the distribution of n1/2(theta(n) - theta) under P(theta,GAMMA)n(P(theta,GAMMA) being the GAMMA-...
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作者：YOHAI, VJ; ZAMAR, RH
作者单位：University of British Columbia
摘要：A natural measure of the degree of robustness of an estimate T is the maximum asymptotic bias B(T)(epsilon) over an epsilon-contamination neighborhood. Martin, Yohai and Zamar have shown that the class of least alpha-quantile regression estimates is minimax bias in the class of M-estimates, that is, they minimize B(T)(epsilon), with a depending on epsilon. In this paper we generalize this result, proving that the least alpha-quantile estimates are minimax bias in a much broader class of estima...
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作者：MAGULURI, G
摘要：Clayton's model for association in bivariate survival data is both of intrinsic importance and an interesting example of a semiparametric estimation problem, that is, a problem where inference about a parameter is required in the presence of nuisance functions. The joint distribution of the two survival times in this model is absolutely continuous and a single parameter governs the association between the two survival times. In this paper we describe an algorithm to derive the asymptotic lower...
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作者：HORVATH, L
摘要：We compute the asymptotic distribution of the maximum likelihood ratio test when we want to check whether the parameters of normal observations have changed at an unknown point. The proof is based on the limit distribution of the largest deviation between a d-dimensional Ornstein-Uhlenbeck process and the origin.
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作者：EVANS, SN; SPEED, TP
摘要：The so-called method of invariants is a technique in the field of molecular evolution for inferring phylogenetic relations among a number of species on the basis of nucleotide sequence data. An invariant is a polynomial function of the probability distribution defined by a stochastic model for the observed nucleotide sequence. This function has the special property that it is identically zero for one possible phylogeny and typically nonzero for another possible phylogeny. Thus it is possible t...
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作者：PUKELSHEIM, F; STUDDEN, WJ
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Purdue University System; Purdue University
摘要：E-optimal designs for the full mean parameter vector, and for many subsets in univariate polynomial regression models are determined. The derivation is based on the interplay between E-optimality and scalar optimality. The scalar parameter systems are obtained as transformations of the coefficient vector c of the Chebyshev polynomial.
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作者：VANDEGEER, S
摘要：Consider a class P = {P(theta) : theta is-an-element-of THETA} of probability measures on a measurable space (K, A), dominated by a sigma-finite measure mu. Let f(theta) = dP(theta)/dmu, theta is-an-element-of THETA, and let theta(n) be a maximum likelihood estimator based on n independent observations from P(theta0), theta0 is-an-element-of THETA). We use results from empirical process theory to obtain convergence for the Hellinger distance h(f(thetan), f(theta0)), under certain entropy condi...
