Message-ID: <4EFD96C5.9070509@alpestat.com>
Date: 2011-12-30T10:47:33Z
From: Yves Deville
Subject: Cholesky update/downdate
In-Reply-To: <CAO7JsnS3z_-1WYB-28DTicbR4E6ABrDtsR3KU01gsPZ6D3GDdg@mail.gmail.com>
Hi Douglas,
thanks for your answer.
My question indeed arises from a sparse matrix context: 'A' is sparse
symmetric, and 'C' must also be sparse since it would otherwise fill.
It comes from a Bayes regression with a very large number of parameters;
a loop over blocks will do the job in my specific case. Yet I wondered
about this since similar need for "covariance updating" may arise from
linear filtering or kriging.
Douglas Bates wrote
> The CHOLMOD library provides sparse matrix methods, especially the
> Cholesky decomposition and modifications to that decomposition, which
> is where the name comes from. Do you expect to work with sparse
> matrices?
>
> I haven't seem too much code for update/downdate operations on the
> Cholesky decomposition for dense matrices. There were rank-1
> update/downdate methods in Linpack but they didn't make it through to
> Lapack.