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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.
Nonasymptotic bounds on the estimation error of MCMC algorithms
Mean square error Computable bounds
2011/7/6
We address the problem of upper bounding the mean square error of MCMC estimators. Our analysis is non-asymptotic.
Relative Density-Ratio Estimation for Robust Distribution Comparison
Density ratio Pearson divergence Outlier detection
2011/7/6
Divergence estimators based on direct approximation of density-ratios without going through separate approximation of numerator and denominator densities have been successfully applied to machine lear...
Nonparametric Regression Estimation with Incomplete Data: Minimax Global Convergence Rates and Adaptivity
Adaptivity Besov spaces inhomogeneous data minimax estimation
2011/7/6
We consider the nonparametric regression estimation problem of recovering an unknown response function $f$ on the basis of incomplete data when the design points follow a known density $g$ with a fini...
Convergence rate for predictive recursion estimation of finite mixtures
Density estimation Kullback–Leibler divergence
2011/7/6
Predictive recursion (PR) is a fast stochastic algorithm for nonparametric estimation of mixing distributions in mixture models.
Dynamic Large Spatial Covariance Matrix Estimation in Application to Semiparametric Model Construction via Variable Clustering: the SCE approach
Time Series Covariance Estimation Regularization, Sparsity
2011/7/6
To better understand the spatial structure of large panels of economic and financial time series and provide a guideline for constructing semiparametric models, this paper first considers estimating a...
Sequential estimation for covariate-adjusted response-adaptive designs
Covariate-adjustment logistic regression response-adaptive design se-quential estimation
2011/7/6
In clinical trials, a covariate-adjusted response-adaptive (CARA) design allows a subject newly entering a trial a better chance of being allocated to a superior treatment regimen based on cumulative ...
Adaptive estimation in the nonparametric random coefficients binary choice model by needlet thresholding
Discrete choice models random coefficients inverse problems
2011/7/6
In this article we consider the estimation of the joint distribution of the random coefficients and error term in the nonparametric random coefficients binary choice model. In this model from economic...
Estimation of covariance matrices based on hierarchical inverse-Wishart priors
Bayesian covariance estimation Skrinkage Hierarchical Inverse-Wishart prior
2011/7/5
This paper focuses on Bayesian shrinkage for covariance matrix estimation. We examine posterior properties and frequentist risks of Bayesian estimators based on new hierarchical inverse-Wishart priors...
Copula representation of bivariate L-moments : A new estimation method for multiparameter 2-dimentional copula models
Copulas Dependence Multivariate L-moments Parametric estimation
2011/7/5
Recently, Serfling and Xiao (2007) extended the L-moment theory (Hosking, 1990) to the multivariate setting.
A CURE for noisy magnetic resonance images: Chi-square unbiased risk estimation
A CURE noisy magnetic resonance images Chi-square unbiased risk estimation
2011/7/5
In this article we derive an unbiased expression for the expected mean-squared error associated with continuously differentiable estimators of the noncentrality parameter of a chi-square random variab...
Dual divergences estimation for censored survival data
Robust estimation Minimum divergence estimators Kaplan-Meier estimator
2011/7/5
This paper is devoted to robust estimation based on dual divergences estimators for parametric models in the framework of right censored data. We give limit laws of the proposed estimators and examine...
Sharp oracle inequalities and slope heuristic for specification probabilities estimation in general random fields
Sharp oracle inequalities slope heuristic specification probabilities estimation
2011/7/5
We provide new methods for estimation of the one-point specification probabilities in general discrete random fields.
Threshold estimation based on a p-value framework in dose-response and regression settings
estimation based p-value framework dose-response regression settings
2011/7/5
We use p-values to identify the threshold level at which a regression function takes off from its baseline value, a problem motivated by applications in toxicological and pharmacological dose-response...