sclr_fit {sclr} | R Documentation |
Fitter function for the scaled logit model
Description
Computing engine behind sclr
.
Usage
sclr_fit(
y,
x,
tol = 10^(-7),
algorithm = c("newton-raphson", "gradient-ascent"),
nr_iter = 2000,
ga_iter = 2000,
n_conv = 3,
conventional_names = FALSE,
seed = NULL
)
Arguments
y |
A vector of observations. |
x |
A design matrix. |
tol |
Tolerance. |
algorithm |
Algorithms to run. "newton-raphson" or "gradient-ascent". If a character vector, the algorithms will be applied in the order they are present in the vector. |
nr_iter |
Maximum allowed iterations for Newton-Raphson. |
ga_iter |
Maximum allowed iterations for gradient ascent. |
n_conv |
Number of times the algorithm has to converge (to work around local maxima). |
conventional_names |
If |
seed |
Seed for the algorithms. |
Details
The likelihood maximisation can use the Newton-Raphson or the gradient ascent algorithms.
[Package sclr version 0.3.1 Index]