glm.test.control: Set up control object for GLM computations

Description Usage Arguments Details Value Author(s) See Also

Description

Several commands depend on fitting a generalized linear model (GLM), using the standard iteratively reweighted least squares (IRLS) algorithm. This function sets various control parameters for this.

Usage

1
glm.test.control(maxit = 20, epsilon = 1.e-5, R2Max = 0.99)

Arguments

maxit

Maximum number of IRLS steps

epsilon

Convergence threshold for IRLS algorithm

R2Max

R-squared limit for aliasing of new terms

Details

Sometimes (although not always), an iterative scheme is necessary to fit a generalized linear model (GLM). The maxit parameter sets the maximum number of iterations to be carried out, while the epsilon parameter sets the criterion for determining convergence. Variables which are judged to be "aliased" are dropped. A variable is judged to be aliased if RSS/TSS is less than (1-R2Max), where

The weights used in this calculation are the "working" weights of the IRLS algorithm.

Value

Returns the parameters as a list in the expected order

Author(s)

David Clayton dc208@cam.ac.uk

See Also

snp.lhs.tests, snp.rhs.tests


NikNakk/snpStats documentation built on May 7, 2019, 6:18 p.m.