make_irls_warmup: Create starting values for iterative reweighted least squares

In hierNest: Penalized Regression with Hierarchical Nested Parameterization Structure

Create starting values for iterative reweighted least squares

Description

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).

Details

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

Value

List of class 'irlsspgl_warmup'

hierNest documentation built on March 24, 2026, 5:07 p.m.