logistf.control {nncc} | R Documentation |
logistf
Sets parameters for Newton-Raphson iteration in Firth's penalized-likelihood logistic regression.
logistf.control(
maxit = 25,
maxhs = 5,
maxstep = 5,
lconv = 1e-05,
gconv = 1e-05,
xconv = 1e-05,
collapse = TRUE
)
logistf.control(
maxit = 25,
maxhs = 5,
maxstep = 5,
lconv = 1e-05,
gconv = 1e-05,
xconv = 1e-05,
collapse = TRUE
)
maxit |
Max iterations |
maxhs |
Maxhs |
maxstep |
Max steps |
lconv |
lconv |
gconv |
gconv |
xconv |
xconv |
collapse |
collapse |
logistf.control()
is used by logistf
and logistftest
to set control parameters to default values.
Different values can be specified, e. g., by logistf(..., control= logistf.control(maxstep=1))
.
maxit |
The maximum number of iterations |
maxhs |
The maximum number of step-halvings in one iteration. The increment of the beta vector within one iteration is divided by 2 if the new beta leads to a decrease in log likelihood. |
maxstep |
Specifies the maximum step size in the beta vector within one iteration. |
lconv |
Specifies the convergence criterion for the log likelihood. |
gconv |
Specifies the convergence criterion for the first derivative of the log likelihood (the score vector). |
xconv |
Specifies the convergence criterion for the parameter estimates. |
collapse |
If |
Georg Heinze
data(sexagg)
fit2<-logistf(case ~ age+oc+vic+vicl+vis+dia, data=sexagg, weights=COUNT,
control=logistf.control(maxstep=1))
summary(fit2)