Nonparametric and Non-Linear Models and Data Mining in time Series: A Case-Study on the Canadian Lynx Data

DOI10.1111/1467-9876.00106zbMath0904.62103OpenAlexW2019306876MaRDI QIDQ4216169

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Publication date: 21 January 1999

Published in: Journal of the Royal Statistical Society Series C: Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/1467-9876.00106

zbMATH Keywords

model selectiondata miningprojection pursuit regressionback-fittingprediction error varianceequivalent degrees of freedom

Mathematics Subject Classification ID

Density estimation (62G07) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Theory of languages and software systems (knowledge-based systems, expert systems, etc.) for artificial intelligence (68T35)

Related Items (5)

Semiparametric approximation methods in multivariate model selection ⋮ Revisiting the Canadian Lynx Time Series Analysis Through TARMA Models ⋮ Average regression surface for dependent data ⋮ A generalization of some classical time series tools ⋮ Forecasting time series using principal component analysis with respect to instrumental variables

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