Thanks to its fine balance between model flexibility and interpretability, the nonparametric additive has been widely used, variable selection for this type of frequently studied. However, none existing solutions can control false discovery rate (FDR) unless sample size tends infinity. The knockoff framework is a recent proposal that address issue, but few are directly applicable models. In art...

In this paper we develop a novel procedure of variable screening for multivariate additive random-effects model, based on B-spline function approximations. With these approximations, the so-called signal-to-noise ratio (SNR) can be defined to inform importance each covariate in model. Then, SNR-based forward filtering is conducted covariates by using iterative projections multiple response data...

BACKGROUND In recent years a great number of studies have applied generalised additive models (GAMs) to time series data to estimate the short term health effects of air pollution. Lately, however, it has been found that concurvity--the non-parametric analogue of multicollinearity--might lead to underestimation of standard errors of the effects of independent variables. Underestimation of stand...

In the present paper we review and extend two stochastic models for loss resenting and study their impact on extensions of the additive method and of the chain-ladder method. The first of these models is a particular linear model while the second one is a sequential model which is composed of a finite number of conditional linear models. These models lead to multivariate extensions of the addit...