Parameter estimation in high dimensional Gaussian distributions

In order to compute the log-likelihood for high dimensional Gaussian models, it is necessary to compute the determinant of the large, sparse, symmetric positive definite precision matrix. Traditional methods for evaluating the log-likelihood, which are typically based on Cholesky factorisations, are...

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Veröffentlicht in:	Statistics and computing 2014-03, Vol.24 (2), p.247-263
Hauptverfasser:	Aune, Erlend, Simpson, Daniel P., Eidsvik, Jo
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial Intelligence Computation Determinants Gaussian Mathematical analysis Mathematical models Mathematics and Statistics Numerical analysis Probability and Statistics in Computer Science Statistical Theory and Methods Statistics Statistics and Computing/Statistics Programs Vectors (mathematics)
Online-Zugang:	Volltext
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