1 citations · 2 across the 7 of their papers we have counts for
13 papers
Analysis of gradual changes in nonparametric regression based on a new optimization method in the non-unique case
Marie Hušková, Natalie Neumeyer, Leonie Selk
Consider a nonparametric regression model with one-dimensional covariates and a continuous regression function. Assume that the regression function from the left of the covariate s…
Goodness-of-fit testing for the error distribution in functional linear models
Natalie Neumeyer, Leonie Selk
We consider the error distribution in functional linear models with scalar response and functional covariate. Different asymptotic expansions of the empirical distribution function…
Testing for changes in the error distribution in functional linear models
Natalie Neumeyer, Leonie Selk
We consider linear models with scalar responses and covariates from a separable Hilbert space. The aim is to detect change points in the error distribution, based on sequential res…
Uniform convergence rates and automatic variable selection in nonparametric regression with functional and categorical covariates
Leonie Selk
In Selk and Gertheiss (2022) a nonparametric prediction method for models with multiple functional and categorical covariates is introduced. The dependent variable can be categoric…
Nonparametric Regression and Classification with Functional, Categorical, and Mixed Covariates
Leonie Selk, Jan Gertheiss
We consider nonparametric prediction with multiple covariates, in particular categorical or functional predictors, or a mixture of both. The method proposed bases on an extension o…
Multivariate boundary regression models
Leonie Selk, Charles Tillier, Orlando Marigliano
In this work, we consider a multivariate regression model with one-sided errors. We assume for the regression function to lie in a general Hölder class and estimate it via a nonpar…
Estimating change points in nonparametric time series regression models
Maria Mohr, Leonie Selk
In this paper we consider a regression model that allows for time series covariates as well as heteroscedasticity with a regression function that is modelled nonparametrically. We…
Semi-parametric transformation boundary regression models
Natalie Neumeyer, Leonie Selk, Charles Tillier
In the context of nonparametric regression models with one-sided errors, we consider parametric transformations of the response variable in order to obtain independence between the…
Specification testing in nonparametric AR-ARCH models
Marie Hušková, Natalie Neumeyer, Tobias Niebuhr +1
In this paper an autoregressive time series model with conditional heteroscedasticity is considered, where both conditional mean and conditional variance function are modeled nonpa…
Hypotheses tests in boundary regression models
Holger Drees, Natalie Neumeyer, Leonie Selk
Consider a nonparametric regression model with one-sided errors and regression function in a general Hölder class. We estimate the regression function via minimization of the local…
Efficient estimation of functionals in nonparametric boundary models
Markus Reiß, Leonie Selk
For nonparametric regression with one-sided errors and a boundary curve model for Poisson point processes we consider the problem of efficient estimation for linear functionals. Th…
Testing for a change of the innovation distribution in nonparametric autoregression - the sequential empirical process approach
Leonie Selk, Natalie Neumeyer
We consider a nonparametric autoregression model under conditional heteroscedasticity with the aim to test whether the innovation distribution changes in time. To this end we devel…
A note on nonparametric testing for Gaussian innovations in AR-ARCH models
Natalie Neumeyer, Leonie Selk
In this paper we consider autoregressive models with conditional autoregressive variance, including the case of homoscedastic AR-models and the case of ARCH models. Our aim is to t…