Analysis of Incomplete Climate Data : Estimation of Mean Values and Covariance Matrices and Imputation of Missing Values

@inproceedings{Schneider2001AnalysisOI,
  title={Analysis of Incomplete Climate Data : Estimation of Mean Values and Covariance Matrices and Imputation of Missing Values},
  author={Tapio Schneider},
  year={2001}
}
Estimating the mean and the covariance matrix of an incomple te dataset and filling in missing values with imputed values i s generally a nonlinear problem, which must be solved iterativel y. The expectation maximization (EM) algorithm for Gaussia n data, an iterative method both for the estimation of mean values and c ovariance matrices from incomplete datasets and for the imp utation of missing values, is taken as the point of departure for the dev lopment of a regularized EM algorithm. In… CONTINUE READING
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