-
作者：BASAWA, IV; MALLIK, AK; MCCORMICK, WP; REEVES, JH; TAYLOR, RL
摘要：Consider a first-order autoregressive process X(t) = beta-X(t-1) + epsilon-t, where {epsilon-t} are independent and identically distributed random errors with mean 0 and variance 1. It is shown that when beta = 1 the standard bootstrap least squares estimate of beta-is asymptotically invalid, even if the error distribution is assumed to be normal. The conditional limit distribution of the bootstrap estimate at beta = 1 is shown to converge to a random distribution.
-
作者：DEJONG, P
摘要：The Kalman recursion for state space models is extended to allow for likelihood evaluation and minimum mean square estimation given states with an arbitrarily large covariance matrix. The extension is computationally minor. Application is made to likelihood evaluation, state estimation, prediction and smoothing.
-
作者：MESSER, K
摘要：It has been observed that to a smoothing spline operator there corresponds an equivalent kernel operator; these two operators have been compared in a variety of norms [Cox (1984), Silverman (1984)]. In this paper, we refine the existing bounds for the particular case of the spline estimator considered in Rice and Rosenblatt (1983) and its corresponding equivalent kernel estimator. We obtain detailed asymptotic expressions for the bias and covariance functions of the two estimates and provide r...
-
作者：DHAR, SK
摘要：In the additive effects outliers (A.O.) model considered here one observes Y(j,n) = X(j) + V(j,n), O less-than-or-equal-to j less-than-or-equal-to n, where {X(j)} is the first order autoregressive [AR(1)] process with the autoregressive parameter \rho\ < 1. The A.O.'s {V(j,n), O less-than-or-equal-to n} are i.i.d. with distribution function (d.f.) (1 - gamma-n)I[x greater-than-or-equal-to 0] + gamma-nL(n)(x), x epsilon R, 0 less-than-or-equal-to gamma-n less-than-or-equal-to 1, where the d.f.'...
-
作者：LOPUHAA, HP; ROUSSEEUW, PJ
作者单位：University of Antwerp
摘要：Finite-sample replacement breakdown points are derived for different types of estimators of multivariate location and covariance matrices. The role of various equivariance properties is illustrated. The breakdown point is related to a measure of performance based on large deviations probabilities. Finally, we show that one-step reweighting preserves the breakdown point.
-
作者：PUKELSHEIM, F; TORSNEY, B
作者单位：University of Glasgow
摘要：An explicit formula is derived to compute the A-optimal design weights on linearly independent regression vectors, for the mean parameters in a linear model with homoscedastic variances. The formula emerges as a special case of a general result which holds for a wide class of optimality criteria. There are close links to iterative algorithms for computing optimal weights.
-
作者：PRUITT, RC
摘要：Conditions under which the bivariate Kaplan-Meier estimate of Dabrowska is not a proper survival function are given. All points assigned negative mass are identified under the assumption that the observations follow an absolutely continuous distribution. The number of points assigned negative mass increases as n2 and the total amount of negative mass does not disappear as n --> infinity, where n is the sample size. A simulation study is reported which shows that large amounts of negative mass ...
-
作者：FENECH, AP; HARVILLE, DA
作者单位：Iowa State University
摘要：We present a general procedure for obtaining an exact confidence set for the variance components in a mixed linear model. The procedure can be viewed as a generalization of the ANOVA method used with balanced models. Our procedure uses, as pivotal quantities, quadratic forms that are distributed independently as chi-squared variables. These quadratic forms are constructed with reference to spaces that are orthogonal with respect to the covariance matrix of the observation vector, which is a fu...
-
作者：JONES, MC; MARRON, JS; PARK, BU
作者单位：Seoul National University (SNU); International Business Machines (IBM); IBM USA; University of North Carolina; University of North Carolina Chapel Hill
摘要：The asymptotically best bandwidth selectors for a kernel density estimator currently require the use of either unappealing higher order kernel pilot estimators or related Fourier transform methods. The point of this paper is to present a methodology which allows the fastest possible rate of convergence with the use of only nonnegative kernel estimators at all stages of the selection process. The essential idea is derived through careful study of factorizations of the pilot bandwidth in terms o...
-
作者：FAN, JQ
摘要：We discuss the difficulties of estimating quadratic functionals based on observations Y(t) from the white noise model Y(t) = integral 0t(f)(u) du + sigma-W(t), t is-an-element-of [0, 1], where W(t) is a standard Wiener process on [0, 1]. The optimal rates of convergence (as sigma --> 0) for estimating quadratic functionals under certain geometric constraints are found. Specifically, the optimal rates of estimating integral 0(1)[f(k)(x)]2 dx under hyperrectangular constraints SIGMA = {f: \x(j)(...
