Fitting of self-exciting threshold autoregressive moving average nonlinear time-series model through genetic algorithm and development of out-of-sample forecasts

DOI10.1080/02331888.2013.822502zbMath1320.37035OpenAlexW1980853423MaRDI QIDQ2934851

Himadri Ghosh, Prajneshu, Sandipan Samanta

Publication date: 22 December 2014

Published in: Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331888.2013.822502

zbMATH Keywords

real-coded genetic algorithmmean square forecasting errormackerel catch dataoptimal out-of-sample forecastSETARMA nonlinear time series model

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Cites Work

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• Multi-step forecasts from threshold ARMA models using asymmetric loss functions
• Testing for threshold autoregression
• On forecasting SETAR processes
• Generalized likelihood ratio statistics and Wilks phenomenon
• A Tukey nonadditivity-type test for time series nonlinearity
• Nonlinearity tests for time series
• Introduction to Genetic Algorithms
• Self Exciting Threshold Autoregressive Models for Describing Cyclical Data
• Using genetic algorithms to parameters \((d,r)\) estimation for threshold autoregressive models

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