Approximate Asymptotic Variance-Covariance Matrix for the Whittle Estimators of GAR(1) Parameters
نویسندگان
چکیده
منابع مشابه
Robust regularized M-estimators of regression parameters and covariance matrix
High dimension low sample size (HD-LSS) data are becoming increasingly present in a variety of fields, including chemometrics and medical imaging. Especially problems with n < p (more variables than measurements) present a challenge to data analysts since the classical techniques can not be used. In this paper, we consider HD-LSS data in regression parameter and covariance matrix estimation pro...
متن کاملAsymptotic algorithm for computing the sample variance of interval data
The problem of the sample variance computation for epistemic inter-val-valued data is, in general, NP-hard. Therefore, known efficient algorithms for computing variance require strong restrictions on admissible intervals like the no-subset property or heavy limitations on the number of possible intersections between intervals. A new asymptotic algorithm for computing the upper bound of the samp...
متن کاملJudging Mcmc Estimators by Their Asymptotic Variance
The expectation of a function can be estimated by the empirical estimator based on the output of a Markov chain Monte Carlo method. We review results on the asymp-totic variance of the empirical estimator, and on improving the estimator by exploiting knowledge of the underlying distribution or of the transition distribution of the Markov chain.
متن کاملAsymptotic expansion of the minimum covariance determinant estimators
In Cator and Lopuhaä [3] an asymptotic expansion for the MCD estimators is established in a very general framework. This expansion requires the existence and non-singularity of the derivative in a first-order Taylor expansion. In this paper, we prove the existence of this derivative for multivariate distributions that have a density and provide an explicit expression. Moreover, under suitable s...
متن کاملAnother Class of Minimax Estimators of A Variance Covariance Matrix in Multivariate Normal Distribution
It is well known that the best equivariant estimator of a variance covari-ance matrix of multivariate normal distribution with respect to the full ane group of transformation is not even minimax. Some minimax estimators have been proposed. Here we treat this problem in the framework of a multivari-ate analysis of variance(MANOVA) model and give other classes of minimax estimators.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Communications in Statistics - Theory and Methods
سال: 2013
ISSN: 0361-0926,1532-415X
DOI: 10.1080/03610926.2011.569862