Abstract Semiparametric regression models have received considerable attention over the last decades, because of their flexibility and good finite sample performances. Here we propose an innovative nonparametric test for linear part models, based on random sign-flipping appropriate transformation residuals, that exploits a spectral decomposition residualizing matrix associated with model. The c...

Motivated by the newly developed max-linear competing copula factor models and max-stable nonlinear time series models, we propose a new class of regression to take advantages easy interpretable features embedded in linear models. It can be seen that relation is special case relation. We develop an EM algorithm based maximum likelihood estimation procedure. The consistency asymptotics estimator...

The single-index model is a statistical for intrinsic regression where responses are assumed to depend on single yet unknown linear combination of the predictors, allowing express function as E[Y|X]=f(⟨v,X⟩) some index vector v and link f. Conditional methods provide simple effective approach estimate by averaging moments X conditioned Y, but parameters whose optimal choice do not generalizatio...