Generalized ordinal patterns in discrete-valued time series: nonparametric testing for serial dependence

DOI10.1080/10485252.2023.2231565MaRDI QIDQ6611224

Christian H. Weiß, Alexander Schnurr

Publication date: 26 September 2024

Published in: Journal of Nonparametric Statistics (Search for Journal in Brave)

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Nonparametric statistical resampling methods (62G09)

Cites Work

• Unnamed Item
• Efficiently measuring complexity on the basis of real-world data
• Cayley permutations
• Asymptotics in statistics: some basic concepts
• Bootstrap methods: another look at the jackknife
• Serial dependence of NDARMA processes
• Modeling zero inflation in count data time series with bounded support
• Non-parametric analysis of serial dependence in time series using ordinal patterns
• Generalized ordinal patterns allowing for ties and their applications in hydrology
• A WARP-SPEED METHOD FOR CONDUCTING MONTE CARLO EXPERIMENTS INVOLVING BOOTSTRAP ESTIMATORS
• STATIONARY DISCRETE AUTOREGRESSIVE-MOVING AVERAGE TIME SERIES GENERATED BY MIXTURES
• Order Patterns in Time Series
• TIME SERIES FROM THE ORDINAL VIEWPOINT
• Theory & Methods: Non‐Gaussian Conditional Linear AR(1) Models
• An Introduction to Discrete‐Valued Time Series
• Softplus INGARCH Model
• First‐order integer valued AR processes with zero inflated poisson innovations
• Some Limit Theorems for Stationary Processes
• Quantiles for Counts
• Symbolic correlation integral
• Non-parametric tests for serial dependence in time series based on asymptotic implementations of ordinal-pattern statistics
• Statistics and contrasts of order patterns in univariate time series

This page was built for publication: Generalized ordinal patterns in discrete-valued time series: nonparametric testing for serial dependence