MldaInvE: Maximum uncertainty Linear Discriminant Analysis inverse matrix estimator.
Description
Builds a well-conditioned estimator for the inverse of a symmetric positive definite matrix, with a
bad-conditioned or singular estimate, based on the Maximum Uncertainty Linear Discriminant Analysis
approach of Thomaz, Kitani and Gillies (2006).
Singular or bad-conditioned estimate of the matrix for which a well-conditioned inverse estimate is sought.
check
Boolean flag indicating if the symmetry of M and the sign of its eigenvalues should be check upfront.
onlyMinv
Boolean flag indicating if only an estimate of the matrix inverse is sought, or if a well-conditioned
approximation to the matrix that M estimates should be returned as well.
numtol
Numerical tolerance.
Value
If onlyMinv is set to true a matrix with the inverse estimate sought. Otherwise a list with components ME and MInvE,
with a well-conditioned approximation to the matrix that M estimates and its inverse.
References
Thomaz, Kitani and Gillies (2006) A maximum uncertainty LDA-based approach for limited sample size problems - with application to face recognition, Journal of the Brazilian Computer Society, 12 (2), 7-18