A New Family of High-Resolution Multivariate Spectral Estimators
نویسندگان
چکیده
منابع مشابه
On the well-posedness of multivariate spectrum approximation and convergence of high-resolution spectral estimators
In this paper, we establish the well-posedness of the generalized moment problems recently studied by Byrnes-Georgiou-Lindquist and coworkers, and by Ferrante-Pavon-Ramponi. We then apply these continuity results to prove almost sure convergence of a sequence of high-resolution spectral estimators indexed by the sample size. ∗Partially supported by the Ministry of Education, University, and Res...
متن کاملHigh Breakdown Multivariate Estimators
In the literature, estimators for regression or multivariate location and dispersion that have been shown to be both consistent and high breakdown are impractical to compute. This paper gives easily computed high breakdown robust √ n consistent estimators, and the applications for these estimators are numerous. For regression, the response plot of the fitted values versus the response is shown ...
متن کاملNew Multivariate Product Density Estimators
where X(k) = (X(k)1, . . . , X(k)d), and X(k) is the k-th nearest neighbor of x when points are ordered by increasing values of the product ∏d j=1 |xj−X(k)j |, and k = o(log n), k → ∞. The auxiliary results needed permit us to formulate universal consistency results (pointwise and in L1) for product kernel estimates with different window widths for each coordinate, and for rectangular partition...
متن کاملStructural shrinkage of nonparametric spectral estimators for multivariate time series
Abstract: In this paper we investigate the performance of periodogram based estimators of the spectral density matrix of possibly high-dimensional time series. We suggest and study shrinkage as a remedy against numerical instabilities due to deteriorating condition numbers of (kernel) smoothed periodogram matrices. Moreover, shrinking the empirical eigenvalues in the frequency domain towards on...
متن کاملMultivariate Outlier Detection With High-Breakdown Estimators
Multivariate Outlier Detection With High-Breakdown Estimators Andrea Cerioli Andrea Cerioli is Professor, Dipartimento di Economia, Sezione di Statistica e Informatica, Università di Parma, Via Kennedy 6, 43100 Parma, Italy . The author expresses his gratitude to three anonymous reviewers for insightful comments that led to many improvements in the article. The author also thanks Marco Riani an...
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: IEEE Transactions on Automatic Control
سال: 2014
ISSN: 0018-9286,1558-2523
DOI: 10.1109/tac.2013.2293218