weib.reg: Weibull regression model

Description Usage Arguments Details Value Author(s) References See Also Examples

Description

Weibull regression model.

Usage

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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 <stefanosfafalios@gmail.com>.

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

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## Not run: 
x <- matrix(rnorm(100 * 2), ncol = 2)
y <- rexp(100, 1)
res<-weib.reg(y, x)

## End(Not run)

Rfast documentation built on Dec. 11, 2021, 9:59 a.m.