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搜索结果: 1-9 共查到high-dimensional regression相关记录9条 . 查询时间(0.124 秒)
In a high dimensional linear regression model, we propose a new procedure for testing statistical significance of a subset of regression coefficients. Specifically,we employ the partial covariances be...
In a high dimensional linear regression model, we propose a new procedure for testing statistical significance of a subset of regression coefficients. Specifically,we employ the partial covariances be...
In a high dimensional linear regression model, we propose a new procedure for testing statistical significance of a subset of regression coefficients. Specifically,we employ the partial covariances be...
We propose simultaneous tests for coefficients in high dimensional linear regression models with factorial designs. The proposed tests are designed for the “large p, small n situations where the conv...
In the high-dimensional regression model a response variable is linearly related to $p$ covariates, but the sample size $n$ is smaller than $p$. We assume that only a small subset of covariates is `ac...
We propose a new method of estimation in high-dimensional linear regression model. It allows for very weak distributional assumptions including heteroscedasticity, and does not require the knowledge o...
We consider a high-dimensional regression model with a possible change-point due to a covariate threshold and develop the Lasso estimator of regression coefficients as well as the threshold parameter....
We study the behavior of the posterior distribution in ultra high-dimensional Bayesian Gaussian linear regression models havingp佲n,withpthe number of predictors and nthe sample size. In particular, ou...
We show that the two-stage adaptive Lasso procedure (Zou, 2006) is consistent for high-dimensional model selection in linear and Gaussian graphical models. Our conditions for consistency cover more ...

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