Low-dimensional decomposition , smoothing and forecasting of sparse functional data

  title={Low-dimensional decomposition , smoothing and forecasting of sparse functional data},
  author={Alexander Dokumentov and Rob J. Hyndman},
We propose a new generic method ROPES (Regularized Optimization for Prediction and Estimation with Sparse data) for decomposing, smoothing and forecasting two-dimensional sparse data. In some ways, ROPES is similar to Ridge Regression, the LASSO, Principal Component Analysis (PCA) and Maximum-Margin Matrix Factorisation (MMMF). Using this new approach, we propose a practical method of forecasting mortality rates, as well as a new method for interpolating and extrapolating sparse longitudinal… CONTINUE READING
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