Create starting values for iterative reweighted least squares

This function may be used to create potentially valid starting values for calling sparsegl() with a stats::family() object. It is not typically necessary to call this function (as it is used internally to create some), but in some cases, especially with custom generalized linear models, it may improve performance.

Usage

make_irls_warmup(nobs, nvars, b0 = 0, beta = double(nvars), r = double(nobs))

Arguments

nobs

Number of observations in the response (or rows in x).

nvars

Number of columns in x

b0

Scalar. Initial value for the intercept.

beta

Vector. Initial values for the coefficients. Must be length nvars (or a scalar).

r

Vector. Initial values for the deviance residuals. Must be length nobs (or a scalar).

Value

List of class irlsspgl_warmup

Details

Occasionally, the irls fitting routine may fail with an admonition to create valid starting values.