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作者：EATON, ML
摘要：Given a parametric model and an improper prior distribution, the formal posterior distribution induces decision rules in any decision problem. The results here provide conditions under which this formal Bayes method produces admissible decision rules for all quadratically regular decision problems. The conditions derived are shown to be equivalent to the recurrence of a natural symmetric Markov chain (on the parameter space) generated by the model and the improper prior. The results are also u...
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作者：SHAO, J; WU, CFJ
作者单位：University of Waterloo
摘要：Inference, including variance estimation, can be made from stratified samples by selecting a balanced set of subsamples. This balanced subsampling method is generically called the balanced repeated replication method in survey data analysis, which includes McCarthy's balanced half-samples method and its extensions for more general stratified designs. We establish the asymptotic consistency of the balanced repeated replication variance estimators when the parameter of interest is the population...
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作者：BURSHTEIN, D; DELLAPIETRA, V; KANEVSKY, D; NADAS, A
作者单位：International Business Machines (IBM); IBM USA
摘要：Let (X, U) be jointly distributed on K X R(n). Let Y = E(U\X) and let U be the convex hull of the range of U. Let C: K --> C = {1, 2, ..., k}, k greater-than-or-equal-to 1, induce a measurable k way partition {K1, ...,K(k)} of K. Define the impurity of K(c) = C-1(c) to be phi(c, E(U\C(X) = c)), where phi: C x U --> R1 is a concave function in its second argument. Define the impurity psi(C) of the partition as the average impurity of its members: psi(C) = Ephi(C(X), E(U\C(X))). We show that for...
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作者：KLONECKI, W; ZONTEK, S
作者单位：Polish Academy of Sciences; Institute of Mathematics of the Polish Academy of Sciences
摘要：Simultaneous estimation of the vector of variance components under unbalanced mixed models w.r.t. the ordinary quadratic lose function is considered. A new method of constructing invariant quadratic admissible estimators, both with and without the condition of unbiasedness, is presented. Using this method, admissible estimators for the factorial models with imbalance at the last stage and the unbalanced (p - 1)-way nested factors design are constructed.
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作者：LAHIRI, SN
摘要：Consider a multiple linear regression model Y(i) = x(i)'beta + epsilon(i), where the epsilon(i)'s are independent random variables with common distribution F and the x(i)'s are known design vectors. Let Beta(n)BAR be the M-estimator of beta corresponding to a score function psi. Under some conditions on F, psi and the x(i)'s, two-term Edgeworth expansions for the distributions of standardized and studentized beta(n)BAR are obtained. Furthermore, it is shown that the bootstrap method is second ...
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作者：MULLER, HG; PREWITT, K
摘要：Adaptive nonparametric kernel estimators for the location of a peak of the spectral density of a stationary time series are proposed and investigated. They are based on direct smoothing of the periodogram where the amount of smoothing is determined automatically in an asymptotically optimal fashion. These adaptive estimators minimize the asymptotic mean squared error. Adaptivity is derived from the weak convergence of a two-parameter stochastic process in a deviation and a bandwidth coordinate...
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作者：SRIRAM, TN
摘要：A sequential procedure for estimating the regression parameter beta is-an-element-of R(k) in a regression model with symmetric errors is proposed. This procedure is shown to have asymptotically smaller regret than the procedure analyzed by Martinsek when beta = 0, and the same asymptotic regret as that procedure when beta not-equal 0. Consequently, even when the errors are normally distributed, it follows that the asymptotic regret can be negative when beta = 0. These results extend a recent w...
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作者：GOLDSTEIN, L; MESSER, K
作者单位：California State University System; California State University Fullerton
摘要：Consider the problem of estimating the value of a functional LAMBDA(f) for f an unknown density or regression function. The straightforward plug-in estimator LAMBDA(f) with f a particular estimate of f achieves the optimal rate of convergence in the sense of Stone over bounded subsets of a Sobolev space for a broad class of linear and nonlinear functionals. For many functionals the rate calculation depends on a Frechet-like derivative of the functional, which may be obtained using elementary c...
