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Global sensitivity analysis of a numerical code, more specifically estimation of Sobol indices associated with input variables, generally requires a large number of model runs.
Astroinformatics of galaxies and quasars: a new general method for photometric redshifts estimation
cosmology observations galaxies:redshifts
2011/7/19
With the availability of the huge amounts of data produced by current and future large multi-band photometric surveys, photometric redshifts have become a crucial tool for extragalactic astronomy and ...
An estimation of distribution algorithm with adaptive Gibbs sampling for unconstrained global optimization
Estimation of distribution algorithms Evolutionary algorithms
2011/7/19
In this paper is proposed a new heuristic approach belonging to the field of evolutionary Estimation of Distribution Algorithms (EDAs). EDAs builds a probability model and a set of solutions is sample...
A Direct Estimation Approach to Sparse Linear Discriminant Analysis
Classification constrained l1-minimization Fisher’s rule
2011/7/19
This paper considers sparse linear discriminant analysis of high-dimensional data. In contrast to the existing methods which are based on separate estimation of the precision matrix $\O$ and the diffe...
We propose a method for nonparametric density estimation that exhibits robustness to contamination of the training sample. This method achieves robustness by combining a traditional kernel density est...
Heavy tailed priors: an alternative to non-informative priors in the estimation of proportions on small areas
Survey Sampling Exponential Family Objective Robust Priors
2011/7/19
We explore the Cauchy and a new heavy tailed (Fuquene, Perez and Pericchi (2011)) priors to estimate proportions on small areas.
Nonparametric estimation of multivariate extreme-value copulas
empirical copula extreme-value copula Pickands dependence function
2011/7/19
Extreme-value copulas arise in the asymptotic theory for componentwise maxima of independent random samples. An extreme-value copula is determined by its Pickands dependence function, which is a funct...
High-Dimensional Structure Estimation in Ising Models: Tractable Graph Families
Graphical model selection Ising models Greedy algorithms
2011/7/19
We consider the problem of high-dimensional Ising (graphical) model selection. We propose a simple algorithm for structure estimation based on the thresholding of the empirical conditional mutual info...
Large information plus noise random matrix models and consistent subspace estimation in large sensor networks
Large information plus noise random matrix models consistent subspace estimation large sensor networks
2011/7/7
In array processing, a common problem is to estimate the angles of arrival of $K$ deterministic sources impinging on an array of $M$ antennas, from $N$ observations of the source signal, corrupted by ...
Semi-Blind System Identification in Wireless Relay Networks via Gaussian Process Iterated Conditioning on the Modes Estimation
Relay networks System Identification Gaussian processes Kernel methods
2011/7/7
This paper presents a flexible stochastic model developed for a class of cooperative wireless relay networks, in which the relay processing functionality is not known at the destination. The challenge...
Widely Linear vs. Conventional Subspace-Based Estimation of SIMO Flat-Fading Channels: Mean-Squared Error Analysis
Subspace-Based Estimation SIMO Flat-Fading Channels: Mean-Squared Error Analysis
2011/7/7
We analyze the mean-squared error (MSE) performance of widely linear (WL) and conventional subspace-based channel estimation for single-input multiple-output (SIMO) flat-fading channels employing bina...
Covariance Estimation for Distributions with 2+εMoments
Covariance Estimation Distributions 2+εMoments
2011/7/7
We study the minimal sample size N=N(n) that suffices to estimate the covariance matrix of an n-dimensional distribution by the sample covariance matrix in the operator norm, and with an arbitrary fix...
Nonparametric Estimation of Second-Order Jump-Diffusion Model
Second-order jump-diffusion N-W estimator Weak consistency
2011/7/6
We study the nonparametric estimators of the infinitesimal coefficients of the second-order jump-diffusion models. Under the mild conditions, we obtain the weak consistency and the asymptotic normalit...
Sparse Inverse Covariance Estimation via an Adaptive Gradient-Based Method
Sparse Covariance Estimation Adaptive Gradient-Based Method
2011/7/6
We study the problem of estimating from data, a sparse approximation to the inverse covariance matrix. Estimating a sparsity constrained inverse covariance matrix is a key component in Gaussian graphi...
k-Nearest neighbor density estimation on Riemannian Manifolds
Asymptotic results Density estimation Meteorological applications
2011/7/6
In this paper, we consider a k-nearest neighbor kernel type estimator when the random variables belong in a Riemannian manifolds.