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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...
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...
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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