Interpolation, realization, and reconstruction of noisy, irregularly sampled data
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Various statistical procedures related to linear prediction and optimal filtering are developed for general, irregularly sampled, data sets. The data set may be a function of time, a spatial sample, or an unordered set. In the case of time series, the underlying process may be low-frequency divergent (weakly nonstationary)