Low-dimensional decomposition, smoothing and forecasting of sparse functional data
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References listed on IDEAS
- Han Lin Shang & Heather Booth & Rob Hyndman, 2011. "Point and interval forecasts of mortality rates and life expectancy: A comparison of ten principal component methods," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 25(5), pages 173-214, July.
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- Alexander Dokumentov & Rob J. Hyndman, 2015. "STR: A Seasonal-Trend Decomposition Procedure Based on Regression," Monash Econometrics and Business Statistics Working Papers 13/15, Monash University, Department of Econometrics and Business Statistics.
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KeywordsTikhonov regularisation; Smoothing; Forecasting; Ridge regression; PCA; LASSO; Maximum-margin matrix factorisation; Mortality rates; Sparse longitudinal data;
- C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
NEP fieldsThis paper has been announced in the following NEP Reports:
- NEP-ALL-2014-06-14 (All new papers)
- NEP-ECM-2014-06-14 (Econometrics)
- NEP-FOR-2014-06-14 (Forecasting)
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