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From the 1 of 10 linked papers with an AI index.

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10 papers

math.ST2026

Testing for correct model specification in copula regression models

Holger Dette, Philip Dörr

The paper introduces a goodness‑of‑fit test for semiparametric copula regression models by measuring a weighted L² distance between the true regression function and its best approx…

stat.ME2026

A portmanteau test for multivariate non-stationary functional time series with an increasing number of lags

Lujia Bai, Holger Dette, Weichi Wu

Multivariate locally stationary functional time series provide a flexible framework for modeling functional data exhibiting both temporal and spatial dependencies while allowing fo…

math.ST2026

A spectral based coefficient of determination for the fit of an MA(q) model

Holger Dette, Sebastian Kühnert

We develop a spectral based coefficient of determination to measure how well the spectral density of a stationary process is represented by the class of MA() models. Using perio…

math.ST2026

Pivotal inference for linear predictions in stationary processes

Holger Dette, Sebastian Kühnert

In this paper we develop pivotal inference for the final (FPE) and relative final prediction error (RFPE) of linear forecasts in stationary processes. Our approach is based on a se…

math.ST2026

Kernel Estimation Of Chatterjee's Dependence Coefficient

Mona Azadkia, Holger Dette

Dette, Siburg, and Stoimenov (2013) introduced a copula-based measure of dependence, which implies independence if it vanishes and is equal to 1 if one variable is a measurable fun…

stat.ME2026

Measuring deviations from spherical symmetry

Lujia Bai, Holger Dette

Most of the work on checking spherical symmetry assumptions on the distribution of the -dimensional random vector has its focus on statistical tests for the null hypothesis…