A common argument against the regression approach is that it is too simple. Real world phenomenons follow non-normal distributions, power laws are everywhere and multivariate relationships possibly ...

We also derive general asymptotic results for QR processes allowing for misspecification of the conditional quantile function, extending earlier results from a single quantile to the entire process.

This paper provides estimation and inference methods for a structural function, such as Conditional Average Treatment ... (ML) tools. We assume that such function can be represented as a conditional ...

A Conditional Expectation Approach to Model Selection and Active Learning under Covariate Shift Abstract: This chapter contains sections titled: Conditional Expectation Analysis of Generalization ...

In this letter, we consider Gaussian approximations of the optimal importance density in sequential importance sampling for nonlinear, non-Gaussian state-space models. The proposed method is based on ...

The GUD package provides probability density functions and sampling algorithms for three key distributions from the General Unimodal Distribution (GUD) family: the Flexible Gumbel (FG) distribution, ...