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Blending Bayesian and frequentist methods according to the precision of prior information with an application to hypothesis testing
blended inference confidence distribution confidence posterior
2011/7/19
The following zero-sum game between nature and a statistician blends Bayesian methods with frequentist methods such as p-values and confidence intervals. Nature chooses a posterior distribution consis...
A Constrained L1 Minimization Approach to Sparse Precision Matrix Estimation
constrained ℓ 1 minimization covariance matrix Frobenius norm Gaus-sian graphical model rate of convergence precision matrix spectral norm
2011/3/21
A constrained L1 minimization method is proposed for estimating a sparse inverse covariance matrix based on a sample of $n$ iid $p$-variate random variables. The resulting estimator is shown to enjoy ...
Improving the precision of classification trees
Bagging kernel density discrimination nearest neighbor pre-diction random forest
2010/11/8
Besides serving as prediction models, classification trees are use-ful for finding important predictor variables and identifying inter-esting subgroups in the data. These functions can be compromised ...
The Importance of Scale for Spatial-Confounding Bias and Precision of Spatial Regression Estimators
Epidemiology, identifiability, mixed model,penalized likelihood random effects spatial correlation splines
2010/11/9
Residuals in regression models are often spatially correlated.Prominent examples include studies in environmental epidemiology to understand the chronic health effects of pollutants.
Adjusted empirical likelihood with high-order precision
Bartlett correction confidence region Edgeworth expansion
2010/10/14
Empirical likelihood is a popular nonparametric or semi-parametric statistical method with many nice statistical properties. Yet when the sample size is small, or the dimension of the accompanying est...
An asymptotic fixed-precision confidence interval for the minimum of a quandratic regression function
An asymptotic fixed-precision confidence interval a quandratic regression function
2009/9/23
An asymptotic fixed-precision confidence interval for the minimum of a quandratic regression function。
Re-considering the variance parameterization in multiple precision models
variance parameterization multiple precision models
2009/9/22
The simplex parameterization has at least two attractive features.
First, it typically leads to simple MCMC algorithms with good mixing proper-
ties regardless of the parameterization used to specif...
On the precision of the spectral profile
uniform mixing time maxing time spectral prole Faber-Krahn inequality rough isometry quasi isometry coarse isometry
2009/6/12
We examine the spectral profile bound of Goel, Montenegro and Tetali - for the L mixing time of continuous-time random walk in reversible settings. We find that it is precise up to a loglog factor, an...