Performs a test of convergence based on the L2 norm of
the change in 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
addreg 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.