Long‐range dependence (LRD) refers to dependence structures that decay slowly with
increasing distance. Mathematically this leads to limit theorems that differ from the short …

This paper proposes a new class of semiparametric generalized long-memory models with
FIAPARCH errors that extends the conventional GARMA model to incorporate nonlinear …

We consider data-adaptive wavelet estimation of a trend function in a time series model with
strongly dependent Gaussian residuals. Asymptotic expressions for the optimal mean …

In the paper a general framework for large scale modeling of macroeconomic and financial
time series is introduced. The proposed approach is characterized by simplicity of …

Motivated by an example from neurobiology, we consider estimation in a spline regression
model with long-range dependent errors that are generated by Gaussian subordination …

We establish the existence of multivariate stationary processes with arbitrary marginal
copula distributions and long-range dependence. The effect of long-range dependence on …

Motivated by the analysis of glomerular time series extracted from calcium-imaging data,
asymptotic theory for piecewise polynomial and spline regression with partially free knots …

We consider nonparametric estimation of an additive time series decomposition into a long‐
term trend μ and a smoothly changing seasonal component S under general assumptions …

In this work we deal with the mathematical analysis and application of piecewise (or
segmented) polynomial regression. Motivated by an application in neurobiology we allow …

This chapter is a collection of short contributions on environmental time series analysis. The
focus is on nonparametric trend estimation, role of nonstationarity vs. long-memory or slowly …