English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

In this paper the nonparametric quantile regression model is considered in alocation-scale context. The asymptotic properties of the empirical independenceprocess based on covariates and estimated residuals are investigated. Inparticular an asymptotic expansion and weak convergence to a Gaussian processare proved. The results can, on the one hand, be applied to test for validityof the location-scale model. On the other hand, they allow to derive variousspecification tests in conditional quantile location-scale models. In detail atest for monotonicity of the conditional quantile curve is investigated. Forthe test for validity of the location-scale model as well as for themonotonicity test smooth residual bootstrap versions of Kolmogorov-Smirnov andCramer-von Mises type test statistics are suggested. We give rigorous proofsfor bootstrap versions of the weak convergence results. The performance of thetests is demonstrated in a simulation study.

The independence process in conditional quantile location-scale models and an application to testing for monotonicity