weib.reg: Weibull regression model

In Rfast: A Collection of Efficient and Extremely Fast R Functions

Weibull regression model

Description

Weibull regression model.

Usage

weib.reg(y, x, tol = 1e-07, maxiters = 100)

Arguments

y	The dependent variable; a numerical vector with strictly positive data, i.e. greater than zero.
x	A matrix with the data, where the rows denote the samples (and the two groups) and the columns are the variables. This can be a matrix or a data.frame (with factors).
tol	The tolerance value to terminate the Newton-Raphson algorithm.
maxiters	The max number of iterations that can take place in each regression.

Details

The function is written in C++ and this is why it is very fast. No standard errors are returned as they are not corectly estimated. We focused on speed.

Value

When full is FALSE a list including:

iters	The iterations required by the Newton-Raphson.
loglik	The log-likelihood of the model.
shape	The shape parameter of the Weibull regression.
be	The regression coefficients.

Author(s)

Stefanos Fafalios

R implementation and documentation: Stefanos Fafalios <[e-mail]>.

References

McCullagh, Peter, and John A. Nelder. Generalized linear models. CRC press, USA, 2nd edition, 1989.

See Also

poisson_only, logistic_only, univglms, regression

Examples

x <- matrix(rnorm(100 * 2), ncol = 2)
y <- rexp(100, 1)
res<-weib.reg(y, x)

Rfast documentation built on Nov. 9, 2023, 5:06 p.m.