Genetic algorithms for the identification of additive and innovation outliers in time series

DOI10.1016/S0167-9473(00)00058-XzbMath1030.62063MaRDI QIDQ5941422

Roberto Baragona, Claudio Calzini, Francesco Battaglia

Publication date: 20 August 2001

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

zbMATH Keywords

Genetic algorithmsAutoregressive moving average (ARMA) processFitness functionInterpolationLinear processOutliers in time series

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (9)

ARMA model order and parameter estimation using genetic algorithms ⋮ Detection and estimation of additive outliers in seasonal time series ⋮ Subset selection in multiple linear regression models: a hybrid of genetic and simulated annealing algorithms ⋮ Applications of optimization heuristics to estimation and modelling problems ⋮ Annealing evolutionary stochastic approximation Monte Carlo for global optimization ⋮ Evolutionary Computation Methods and their applications in Statistics ⋮ Classification tree analysis using TARGET ⋮ Annealing evolutionary stochastic approximation Monte Carlo for global optimization ⋮ Forecasting container throughput of Qingdao Port with a hybrid model

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