For a nice example of the data augmentation approach to handling missing data, I would take a look at Nondas’s poster on the Log(N)-Log(S) estimation problem. It’s a nice, relatively direct application of the procedure to a problem involving incompleteness.

]]>btw, wavdetect uses iterative mean imputation to determine the background under a source. Other wavelet-based astro detection algorithms (such as pwdetect) use zero imputation. (i.e., find outliers, excise them from the data, and replace with either mean of the surrounding, or with zero, and iterate until convergence.)

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