R: Weibull regression model

Weibull regression model {Rfast} | R Documentation

## 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 <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

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

    ## End(Not run)

[Package Rfast version 2.0.0 Index]