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In the era of big data, many sparse linear discriminant analysis methods have been proposed for the classification and variable selection of the high-dimensional data. In order to solve the multiclass...
An integral part of many algorithms for S-estimators of linear regression is random subsam-pling. For problems with only continuous predictors simplerandom subsampling is a reliable method to generate...
This note introduces the method of cross-conformal prediction, which is a hybrid of the methods of inductive conformal prediction and cross-validation, and studies its validity and predictive eciency...
This paper studies nonparametric regression with long memory (LRD) errors and predictors. First, we formulate general conditions which guarantee the standard rate of convergence for a nonparametric ke...
Under what conditions is an edge present in a social network at time t likely to decay or persist by some future time t + Delta(t)? Previous research addressing this issue suggests that the network ra...
In this article we study the estimation of the location of jump points in the first derivative (referred to as kinks) of a regression function μ in two random design models with different long-range...
In biomedical studies, researchers are often interested in assessing the association between one or more ordinal explanatory variables and an outcome variable, at the same time adjusting for covariate...
The paper provides several lower bounds and an upper bound for the Bayes risk in statistical prediction theory. The bounds depend on the Fisher information or the bias of the Bayes predictor. The r...
This paper treats a statistical prediction problem under the ordered parameters. An improvement on the best equivariant predictor is discussed for the location family and the scale family.
Conformal predictors, introduced by Vovk et al. [16], serve to build prediction intervals by exploiting a notion of conformity of the new data point with previously observed data. In the present pap...

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