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41,888
Prediction in invertible linear processes
"... We construct rootn consistent plugin estimators for conditional expectations of the form E(h(Xn+1,..., Xn+m)X1,..., Xn) in invertible linear processes. More specifically, we prove a Bahadur type representation for such estimators, uniformly over certain classes of not necessarily bounded functi ..."
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We construct rootn consistent plugin estimators for conditional expectations of the form E(h(Xn+1,..., Xn+m)X1,..., Xn) in invertible linear processes. More specifically, we prove a Bahadur type representation for such estimators, uniformly over certain classes of not necessarily bounded
Efficient Estimation in Invertible Linear Processes
"... An invertible causal linear process is a process which has infinite order moving average and autoregressive representations. We assume that the coefficients in these representations depend on a Euclidean parameter, while the corresponding innovations have an unknown centered distribution with some m ..."
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Cited by 7 (7 self)
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An invertible causal linear process is a process which has infinite order moving average and autoregressive representations. We assume that the coefficients in these representations depend on a Euclidean parameter, while the corresponding innovations have an unknown centered distribution with some
Improved density estimators for invertible linear processes
 Communications in Statistics, Theory & Methods
, 2009
"... Key Words: Convolution estimator; plugin estimator; local Ustatistic; empirical likelihood for dependent data; empirical likelihood with infinitely many constraints; infiniteorder moving average process; infiniteorder autoregressive process. The stationary density of a centered invertible linea ..."
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Cited by 4 (2 self)
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Key Words: Convolution estimator; plugin estimator; local Ustatistic; empirical likelihood for dependent data; empirical likelihood with infinitely many constraints; infiniteorder moving average process; infiniteorder autoregressive process. The stationary density of a centered invertible
Uniformly rootn consistent density estimators for weakly dependent invertible linear processes
 Ann. Statist
, 2007
"... Convergence rates of kernel density estimators for stationary time series are well studied. For invertible linear processes, we construct a new density estimator that converges, in the supremum norm, at the better, parametric, rate n −1/2. Our estimator is a convolution of two different residualbas ..."
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Cited by 12 (9 self)
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Convergence rates of kernel density estimators for stationary time series are well studied. For invertible linear processes, we construct a new density estimator that converges, in the supremum norm, at the better, parametric, rate n −1/2. Our estimator is a convolution of two different residual
Rootn consistency in weighted L1spaces for density estimators of invertible linear processes
, 2008
"... Abstract. The stationary density of an invertible linear processes can be estimated at the parametric rate by a convolution of residualbased kernel estimators. We have shown elsewhere that the convergence is uniform and that a functional central limit theorem holds in the space of continuous functi ..."
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Cited by 8 (8 self)
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Abstract. The stationary density of an invertible linear processes can be estimated at the parametric rate by a convolution of residualbased kernel estimators. We have shown elsewhere that the convergence is uniform and that a functional central limit theorem holds in the space of continuous
Parallel Numerical Linear Algebra
, 1993
"... We survey general techniques and open problems in numerical linear algebra on parallel architectures. We first discuss basic principles of parallel processing, describing the costs of basic operations on parallel machines, including general principles for constructing efficient algorithms. We illust ..."
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Cited by 773 (23 self)
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We survey general techniques and open problems in numerical linear algebra on parallel architectures. We first discuss basic principles of parallel processing, describing the costs of basic operations on parallel machines, including general principles for constructing efficient algorithms. We
An iterative method for the solution of the eigenvalue problem of linear differential and integral
, 1950
"... The present investigation designs a systematic method for finding the latent roots and the principal axes of a matrix, without reducing the order of the matrix. It is characterized by a wide field of applicability and great accuracy, since the accumulation of rounding errors is avoided, through the ..."
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Cited by 537 (0 self)
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the process of "minimized iterations". Moreover, the method leads to a well convergent successive approximation procedure by which the solution of integral equations of the Fredholm type and the solution of the eigenvalue problem of linear differential and integral operators may be accomplished. I.
GMRES: A generalized minimal residual algorithm for solving nonsymmetric linear systems
 SIAM J. SCI. STAT. COMPUT
, 1986
"... We present an iterative method for solving linear systems, which has the property ofminimizing at every step the norm of the residual vector over a Krylov subspace. The algorithm is derived from the Arnoldi process for constructing an l2orthogonal basis of Krylov subspaces. It can be considered a ..."
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Cited by 2076 (41 self)
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We present an iterative method for solving linear systems, which has the property ofminimizing at every step the norm of the residual vector over a Krylov subspace. The algorithm is derived from the Arnoldi process for constructing an l2orthogonal basis of Krylov subspaces. It can be considered
A Signal Processing Approach To Fair Surface Design
, 1995
"... In this paper we describe a new tool for interactive freeform fair surface design. By generalizing classical discrete Fourier analysis to twodimensional discrete surface signals  functions defined on polyhedral surfaces of arbitrary topology , we reduce the problem of surface smoothing, or fai ..."
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Cited by 654 (15 self)
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, or fairing, to lowpass filtering. We describe a very simple surface signal lowpass filter algorithm that applies to surfaces of arbitrary topology. As opposed to other existing optimizationbased fairing methods, which are computationally more expensive, this is a linear time and space complexity algorithm
Automatically tuned linear algebra software
 CONFERENCE ON HIGH PERFORMANCE NETWORKING AND COMPUTING
, 1998
"... This paper describes an approach for the automatic generation and optimization of numerical software for processors with deep memory hierarchies and pipelined functional units. The production of such software for machines ranging from desktop workstations to embedded processors can be a tedious and ..."
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Cited by 478 (26 self)
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and time consuming process. The work described here can help in automating much of this process. We will concentrate our e orts on the widely used linear algebra kernels called the Basic Linear Algebra Subroutines (BLAS). In particular, the work presented here is for general matrix multiply, DGEMM. However
Results 1  10
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41,888