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Robust linear regression through PAC-Bayesian truncation
Linear regression Generalization error Shrinkage
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2010/10/14
We consider the problem of predicting as well as the best linear combination of d given functions in least squares regression under $L^\infty$ constraints on the linear combination. When the input dis...
Limits of truncation experiments
Statistical experiment truncation model Gaussian experiment local asymptotic normality
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2009/9/21
Given n i.i.d. copies XI, . .., X, of a random variable
X with distribution PA, 9 E 8 c g, we are only interested in those
observations that fall into some set D = D (n) c R' having but a smd
proba...
A strong uniform convergence rate of a kernel conditional quantile estimator under random left-truncation and dependent data
Kernel estimator quantile function rate of convergence strong mixing strong uniform consistency truncated data
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2009/9/16
In this paper we study some asymptotic properties of the kernel conditional quantile estimator with randomly left-truncated data which exhibit some kind of dependence. We extend the result obtained by...
Risk bounds in linear regression through PAC-Bayesian truncation
Linear regression Generalization error Shrinkage PAC-Bayesian theorems Risk bounds Robust statistics Resistant estimators
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2010/3/18
We consider the problem of predicting as well as the best linear combination
of d given functions in least squares regression, and variants of this problem including
constraints on the parameters of...