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作者：Niu, XF
作者单位：State University System of Florida; Florida State University
摘要：Consider a space-time stochastic process Z(t)(x) = S(x)+ xi(t)(x) where S(x) is a signal process defined on R-d and xi(t)(x) represents measurement errors at time t. For a known measurable function v(x) on R-d and a fixed cube D subset of R-d, this paper proposes a linear estimator for the stochastic integral integral(D) v(x)S(x)dx based on space-time observations {Z(t)(x(i)): i = 1,..., n; t = 1,..., T}. Under mild conditions, the asymptotic properties of the mean squared error of the estimat...
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作者：Barron, A; Hengartner, N
作者单位：Yale University
摘要：The asymptotic risk of efficient estimators with Kullback-Leibler loss in smoothly parametrized statistical models is k/2n, where k is the parameter dimension and n is the sample size. Under fairly general conditions, we given a simple information-theoretic proof that the set of parameter values where any arbitrary estimator is superefficient is negligible. The proof is based on a result of Rissanen that codes have asymptotic redundancy not smaller than (k/2)log n, except in a set of measure 0.
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作者：Kushner, HB
作者单位：Nathan Kline Institute for Psychiatric Research
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作者：Bischoff, W
作者单位：Helmholtz Association; Karlsruhe Institute of Technology
摘要：Let a linear regression be given. For detecting change-points, it is usual to consider the sequence of partial sums of least squares residuals whence a partial sums process is defined. Given a sequence of exact experimental designs, we consider for each design the corresponding partial sums process. If the sequence of designs converges to a continuous design, we derive the explicit form of the limit process of the corresponding sequence of partial sums processes. This is a complicated function...
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作者：Klein, A; Mélard, G; Zahaf, T
作者单位：University of Amsterdam; Universite Libre de Bruxelles
摘要：In this paper, the computation of the exact Fisher information matrix of a large class of Gaussian time series models is considered. This class, which is often called the single-input-single-output (SISO) model, includes dynamic regression with autocorrelated errors and the transfer function model, with autoregressive moving average errors. The method is based on a combination of two computational procedures: recursions for the covariance matrix of the derivatives of the state vector with resp...
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作者：Ren, JJ; Gu, MG
作者单位：Tulane University; McGill University
摘要：The M-estimators are proposed for the linear regression model with random design when the response observations are doubly censored. The proposed estimators are constructed as some functional of a Campbell-type estimator (F) over cap(n) for a bivariate distribution function based on data which are doubly censored in one coordinate. We establish strong uniform consistency and asymptotic normality of (F) over cap(n) and derive the asymptotic normality of the proposed regression M-estimators thro...
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作者：Díaz-García, JA; Jáimez, RG
作者单位：University of Granada
摘要：Uhlig proposes two conjectures. The first concerns the Jacobian of the transformation Y = B X B' where B is the matrix m x m and m and X, Y belong to the class of positive semidefinite matrices of the order of m X m of rank n < m, S-m,n(+). The second is concerned with the singular multivariate Beta distribution. This article seeks to prove the two conjectures. The latter result is then extended to the case of the singular multivariate F distribution, and the respective density functions are l...
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作者：Koshevoy, G; Mosler, K
作者单位：Russian Academy of Sciences; Central Economics & Mathematics Institute RAS; University of Cologne
摘要：A family of trimmed regions is introduced for a probability distribution in Euclidean d-space. The regions decrease with their parameter Lu, from the closed convex hull of support (at alpha = 0) to the expectation vector (at alpha = 1). The family determines the underlying distribution uniquely. For every cu the region is affine equivariant and continuous with respect to weak convergence of distributions. The behavior under mixture and dilation is studied. A new concept of data depth is introd...
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作者：Bilias, Y; Gu, MG; Ying, ZL
作者单位：Iowa State University; McGill University; Rutgers University System; Rutgers University New Brunswick
摘要：A general asymptotic theory is established for the two-parameter Cox score process with staggered entry data. It extends in several directions the existing theory developed by Sellke and Siegmund, Slud and Gu and Lai. An essential tool employed here is a modern empirical process theory, as elucidated in a recent monograph by Pollard.
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作者：Dahlhaus, R
作者单位：Ruprecht Karls University Heidelberg
摘要：A general minimum distance estimation procedure is presented for nonstationary time series models that have an evolutionary spectral representation. The asymptotic properties of the estimate are derived under the assumption of possible model misspecification. For autoregressive processes with time varying coefficients, the estimate is compared to the least squares estimate. Furthermore, the behavior of estimates is explained when a stationary model is fitted to a nonstationary process.
