my.loop: Iterative loop for calculating the optimal coefficients 'v'.
Description
Calculating the optimal coefficients 'v' iteratively, using quadratic programing.
Usage
my.loop(penden.env)
Arguments
penden.env
Containing all information, environment of pencopula()
Value
liste
The results of each iteration are written in a matrix called 'liste',
saved in the environment. 'liste' contains the penalized
log-likelihood, the log-likelihood, 'lambda' and the weights 'v'.
Details
'my.loop' optimates the log-likelihhod iteratively. Therefore, the
routine checks a) the relative chance in the optimal lambda and stops the
iteration, if the relative change of lambda is less than one
percent. During the calculations of new weights 'v' in the routine
'new.weights', most of the values are called '.temp'. This add on
underlines the temporarily values. Alternatively b) for fixed lambda, 'my.loop' checks the relative
change in the weights. If the change of a) the optimal lambda or b)
of the basis coefficients 'v' are greater than one percent, the
the real values are overwritten with the '.temp' values.
References
Flexible Pair-Copula Estimation in D-vines using Bivariate Penalized
Splines, Kauermann G. and Schellhase C. (2014+), Statistics and Computing (to appear).