cholhilb

Cholesky factorization of the Hilbert matrix of order n

Description

The Hilbert matrix is extremely ill-conditioned, hence cannot be factorized by standard algorithms. However, an analytic solution for its Cholesky factorization exists, which has not been included in the current MATLAB function library.

• MATLAB release: MATLAB 7.1.0 (R14SP3)

[John D'Errico]

It indeed does produce a Cholesky factor, although the transpose of what chol would return. (Why does anyone need a hilbert matrix Cholesky factor?) I did verify that it is a valid Cholesky factor UP to n = 98, far beyond what chol can do. For n = 99 and above it began to generate some NaNs in the matrix. So beware the test cases in the help that show the use of cholhilb for n = 100 or even 1000.

[Yi Cao]

On my machine (XP, MATLAB 7.1), it works upto n=171 without any NaNs although beyond n=85, there are zeros in the diagnal. The need for the Cholesky factor of a Hilbert matrix comes from a least square optimization problem, where the original objective function is J=integral of 0.5z(x)'z(x)dx and z(x) is a nth order polynomial of x and its coefficients are nonlinear functions of decision variables to be optimized. This problem can be represented as a nonlinear least square problem, i.e. J=0.5X'HX, where X is a coefficient matrix of z(x) and H is the Hilbter matrix. Therefore, to solve the nonlinear least square problem, we need the Cholesky factor of the Hilbert matrix.

[John D'Errico]

Thanks for the explanation. Its apparent there is either a matlab release or OS related difference in this. But n=98 or 171 is still a serious improvement over the point where the direct chol(hilb(n)) gives up. chol only got as far as n=12 for me.

[V. Poor]