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Estimator for Number of Sources using Minimum Description Length Criterion for Blind Sparse Source Mixtures
Minimum Description Length Criterion Blind Sparse Source Mixtures
2015/9/29
In this paper I present a Minimum Description Length Estimator for number of sources in an anechoic mixture of sparse signals.The criterion is roughly equal to the sum of negative normalized maximum l...
Information Theory Based Estimator of the Number of Sources in a Sparse Linear Mixing Model
Information Theory Estimator of the Number of Sources Sparse Linear Mixing Model
2015/9/29
In this paper we present an Information Theoretic Estimator for the number of sources mutuallydisjoint in a linear mixing model. The approach follows the Minimum Description Length prescription and is...
A Unified Near-Optimal Estimator For Dimension Reduction in lα (0 < α ≤ 2) Using Stable Random Projections
Near-Optimal Estimator Dimension Reduction Stable Random Projections
2015/8/21
Many tasks (e.g., clustering) in machine learning only require the lα distances instead of the original data. For dimension reductions in the lα norm (0 < α ≤ 2), the method of stable random projectio...
Comments on "Confidence distribution, the frequentist distribution estimator of a parameter --- a review" by Min-ge Xie and Kesar Singh
the frequentist distribution estimator parameter Min-ge Xie Kesar Singh Statistics Theory
2012/6/29
This note is a discussion of the paper "Confidence distribution" by Min-ge Xie and Kesar Singh, to appear in the International Statistical Review.
Adaptive semiparametric wavelet estimator and goodness-of-fit test for long memory linear processes
Long range dependence linear processes wavelet estimator semiparametric estimator
2011/1/18
This paper is first devoted to study an adaptive wavelet based estimator of the long memory parameter for linear processes in a general semi-parametric frame. This is an extension of Bardet et al. (20...
A posteriori error estimator based on gradient recovery by averaging for convection-diffusion-reaction problems approximated by discontinuous Galerkin methods
averaging convection-diffusion-reaction problems discontinuous Galerkin methods
2010/11/9
We consider some (anisotropic and piecewise constant) convection-diffusion-reaction problems in domains of R2, approximated by a discontinuous Galerkin method with polynomials of any degree. We propos...
An efficient estimator for locally stationary Gaussian long-memory processes
efficient estimator Gaussian long-memory processes
2010/11/18
This paper addresses the estimation of locally stationary long-range dependent processes, a methodology that allows the statistical analysis of time series data exhibiting both nonstationarity and str...
A Cyber Security Study of a SCADA Energy Management System: Stealthy Deception Attacks on the State Estimator
A Cyber Security Study SCADA Energy Management System
2010/11/15
The electrical power network is a critical infrastructure in today's society, so its safe and reliable operation is of major concern. State estimators are commonly used in power networks, for example,...
Asymptotic normality of Hill Estimator for truncated data
heavy tails truncation second order regular variation
2010/12/9
The problem of estimating the tail index from truncated data is addressed in Chakrabarty and Samorodnitsky (2009). In that paper, a sample based (and hence random) choice of k is uggested,and it is sh...
A Lower Bound on the Estimator Variance for the Sparse Linear Model
Sparsity parameter estimation sparse linear model denoising
2010/12/8
We study the performance of estimators of a sparse nonrandom vector based on an observation which is linearly transformed and corrupted by additive white Gaussian noise.
Nonnegative-definite covariance structures for which the least squares estimator is the best linear unbiased estimator
Nonnegative-definite covariance structures the least squares estimator
2010/9/15
For the Gauss-Markov model with E(y) = Xβ and Var(y) = V,we establish a new explicit characterization of the general nonnegative-definite covariance structure V such that the best
linear unbiased est...
Recursive Least Squares Estimator with Multiple Exponential Windows in Vector Autoregression
exponential window rectangular window
2007/12/11
In the parameter tracking of time-varying systems, the ordinary method is weighted least squares with the rectangular window or the exponential window. In this paper we propose a new kind of sliding w...
The Minimax Estimator of Stochastic Regression Coecients and Parameters in the Class of All Estimators
minimax estimator stochastic regression coefficients quadratic loss function normal linear model
2007/12/11
In this paper, the authors address the problem of the minimax estimator of linear combinations of stochastic regression coefficients and parameters in the general normal linear model with random effec...
Generalized Inverse Estimator and comparison with Least Squares Estimator
Inverse Estimator Least Squares Estimator
2010/3/4
Trenkler [13] described an iteration estimator. This estimator is defined as follows: for 0 < g < 1/li \max \[ \hat{b}m, g = g \summi=0 (1-g X'X)i X'y , \] where li are eigenvalues of X'X. In this pap...