logbin (version 1.0)

conv.test: Convergence Test Based on L2 Norm

Description

Performs a test of convergence based on the relative change in L2 norm of the parameter estimates.

Usage

conv.test(theta1, theta2, epsilon)

Arguments

theta1

vector of parameter estimates at previous step.

theta2

vector of parameter estimates at current step.

epsilon

positive convergence tolerance.

Value

• A logical; TRUE if sqrt(sum((theta1-theta2)**2))/sqrt(sum(theta1**2)) < epsilon, FALSE otherwise.

Details

This is used as the convergence test in the logbin fitting functions, because the EM algorithm may converge slowly such that the test based on the deviance used in glm.fit (see glm.control) may report convergence at a point away from the actual optimum.

Examples

theta.old <- c(-4,-5,-6)
theta.new <- c(-4.05,-5,-6)

conv.test(theta.old, theta.new, 0.01)
conv.test(theta.old, theta.new, 0.005)