Description

SVD that traps errors and switches to QR when necessary

Usage

Arguments

Details

This function traps errors in the svd function due to numerically zero singular values, and replaces the operation with a QR decomposition. Technically, the R component of the decomposition fails the orthogonality constraint required for the SVD decomposition, but this function exists to save bootstraps from rudely failing; since the critical component of the SVD (in this application) is the left orthogonal matrix, this is a reasonable approximation for bootstrap purposes. If there are too many svd failures (which will will be reported by the function) then it is worth looking into the design matrix.

Value

A list as in what svd produces: U and V matrices as well as the d vector of singular values.

Author(s)

E. Andres Houseman

See Also

svd