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作者：STUTE, W
摘要：In the left-truncation model, one observes data (X(i), Y(i)) only when Y(i) less-than-or-equal-to X(i). Let F denote the marginal d.f. of X(i), the variable of interest. The nonparametric MLE F(n) of F aims at reconstructing F from truncated data. In this paper an almost sure representation of F(n). is derived with improved error bounds on the one hand and under weaker distributional assumptions on the other hand.
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作者：ZHANG, P
摘要：A natural extension of the simple leave-one-out cross validation (CV) method is to allow the deletion of more than one observations. In this article, several notions of the multifold cross validation (MCV) method have been discussed. In the context of variable selection under a linear regression model, we show that the delete-d MCV criterion is asymptotically equivalent to the well known FPE criterion. Two computationally more feasible methods, the r-fold cross validation and the repeated lear...
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作者：BOOTH, JG; HALL, P; WOOD, ATA
作者单位：Commonwealth Scientific & Industrial Research Organisation (CSIRO)
摘要：We show that the method of importance resampling, introduced by Vernon Johns and Anthony Davison, may be enhanced by balancing the resamples. It is demonstrated that ''balanced importance resampling'' improves on both ''balanced uniform resampling'' and ''random importance resampling'', from the viewpoint of statistical efficiency. Moreover, the range of applications for which efficient resampling methods may be applied is extended to include statistics which are smooth functions of solutions ...
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作者：LIU, RC; BROWN, LD
摘要：In many nonparametric problems, such as density estimation, nonparametric regression and so on, all the existing informative estimators are biased (asymptotic or finite sample). There has long been a suspicion that either informative unbiased estimators do not exist for such problems or they must be quite complicated. In this paper, we clarify the nonexistence of informative unbiased estimators in all singular problems both for fixed sample size and asymptotically (this includes most problems ...
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作者：ARAS, G; WOODROOFE, M
作者单位：University of Michigan System; University of Michigan
摘要：Let S1, S2, ... denote a driftless random walk with values in an inner product space W; let Z1, Z2, ... denote a perturbed random walk of the form Z(n) = n + [c, S(n)] + xi(n), n = 1, 2, ..., where xi1, xi2, ... are slowly changing, [. , .] denotes the inner product, and c is-an-element-of W; and let t = t(alpha) = inf{n greater-than-or-equal-to 1: Z(n) > a} for 0 less-than-or-equal-to a < infinity. Conditions are developed under which the first four moments of X(t)BAR, := S(t)/t have asymptot...
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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：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...
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作者：GU, C; QIU, CF
摘要：In this article, a class of penalized likelihood probability density estimators is proposed and studied. The true log density is assumed to be a member of a reproducing kernel Hilbert space on a finite domain, not necessarily univariate, and the estimator is defined as the unique unconstrained minimizer of a penalized log likelihood functional in such a space. Under mild conditions, the existence of the estimator and the rate of convergence of the estimator in terms of the symmetrized Kullback...
