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Distributional Results for Thresholding Estimators in High-Dimensional Gaussian Regression Models
Markov chain Monte Carlo Hamiltonian dynamics Bayesian analysis
2011/7/6
We study the distribution of hard-, soft-, and adaptive soft-thresholding estimators within a linear regression model where the number of parameters k can depend on sample size n and may diverge with ...
On improved estimation in a conditionally Gaussian regression
Conditionally Gaussian regression model Improved estimation James–Stein procedure Non-Gaussian Ornstein–Uhlenbeck process
2011/6/20
The paper considers the problem of estimating a p ≥ 2 dimensional
mean vector of a multivariate conditionally normal distribution under
quadratic loss. The problem of this type arises when estimatin...
Simultaneous estimation of the mean and the variance in heteroscedastic Gaussian regression
Gaussian regression heteroscedasticity model selection Kullback risk convergence rate
2009/9/16
Let $Y$ be a Gaussian vector of $R^{n}$ of mean $s$ and diagonal covariance matrix $Gamma$. Our aim is to estimate both $s$ and the entries $sigma_{i}=Gamma_{i,i}$, for $i=1,dots,n$, on the basis of t...
