Measuring serial dependence in categorical time series

DOI10.1007/s10182-008-0055-4zbMath1171.62055OpenAlexW2052048969MaRDI QIDQ732233

Christian H. Weiß, Rainer Göb

Publication date: 9 October 2009

Published in: AStA. Advances in Statistical Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10182-008-0055-4

zbMATH Keywords

weak stationaritycategorical time seriesdiscrete ARMA processesserial association

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Stationary stochastic processes (60G10)

Related Items

Serial dependence of NDARMA processes ⋮ Coherent forecasting for stationary time series of discrete data ⋮ Generalized binary vector autoregressive processes ⋮ Modeling normalcy‐dominant ordinal time series: An application to air quality level ⋮ Serial dependence and regression of Poisson INARMA models ⋮ Time series analysis of categorical data using auto-odds ratio function ⋮ Moments and cumulants of a mixture ⋮ Empirical measures of signed serial dependence in categorical time series ⋮ Generalized choice models for categorical time series ⋮ Visual analysis of categorical time series ⋮ Auto-association measures for stationary time series of categorical data ⋮ Bayesian comparative study on binary time series ⋮ Distance-Based Analysis of Ordinal Data and Ordinal Time Series

Uses Software

• itsmr

Cites Work

• Coping with nonstationarity in categorical time series
• Measures of association for cross classifications
• STATIONARY DISCRETE AUTOREGRESSIVE-MOVING AVERAGE TIME SERIES GENERATED BY MIXTURES
• On Some Criteria for Estimating the Order of a Markov Chain
• The Measurement of Mobility
• Introduction to Time Series and Forecasting
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