How To Find A Valid Covariance Matrix
In some applications (e.g. building data models from only partially observed data) one wants to find the “nearest” covariance matrix to a given symmetric matrix (e.g. of observed covariances). In 2002, Higham formalized the notion of nearness using a weighted Frobenius norm and provided a method for computing the nearest covariance matrix.
Read more about this topic: Covariance Matrix
Famous quotes containing the words find, valid and/or matrix:
“Somewhere between the overly intrusive parent and the parent who forgets about us after we’re out of the house is the ideally empathetic parent who recognizes the relativity of choice, the errors of his or her own way, and our need to find our own way and who can stay with us at a respectful distance while we do it.”
—Roger Gould (20th century)
“Just as soon as we notice that someone has to force himself to pay attention when dealing and talking with us, we have a valid demonstration that he does not love us or that he does not love us anymore.”
—Friedrich Nietzsche (1844–1900)
“In all cultures, the family imprints its members with selfhood. Human experience of identity has two elements; a sense of belonging and a sense of being separate. The laboratory in which these ingredients are mixed and dispensed is the family, the matrix of identity.”
—Salvador Minuchin (20th century)