lb_auglag {lb} | R Documentation |
auglag
from the alabama PackageFitting Log-Binomial Models with auglag
from the alabama Package
lb_auglag(x, y, start, tol = 1e-07, ceps = 1e-07, control = list(), control.optim = list(), implementation = c("improved", "naive"))
x |
design matrix of dimension |
y |
vector of observations of length |
start |
numeric (vector) starting value (of length p). |
tol |
a numeric giving the tolerance for convergence of the outer iterations
(see |
ceps |
epsilon subtracted from the right hand side (X β ≤q 0 - ceps). Since the inequality X β ≤q 0 is only fullfilled to a certain tolerance we have to substact epsilon to ensure X β ≤q 0. |
control |
passed to |
control.optim |
passed to |
implementation |
a character string choosing which implementation of the log-likelihood and gradient is used. |
the optimization result.