Penalized Covariance Matrix Estimation using a Matrix-Logarithm Transformation

Abstract

For statistical inferences that involve covariance matrices, it is desirable to obtain an accurate covariance matrix estimate with a well-structured eigen-system. We propose to estimate the covariance matrix through its matrix logarithm based on an approximate log-likelihood function. We develop a generalization of the Leonard and Hsu (1992) log-likelihood… (More)

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