# gammareg: Gamma regression with a log-link In Rfast: A Collection of Efficient and Extremely Fast R Functions

## Usage

 ```1 2``` ```gammareg(y, x, tol = 1e-07, maxiters = 100) gammacon(y, tol = 1e-08, maxiters =50) ```

## Arguments

 `y` The dependent variable, a numerical variable with non negative numbers. `x` A matrix or data.frame with the indendent variables. `tol` The tolerance value to terminate the Newton-Raphson algorithm. `maxiters` The maximum number of iterations that can take place in the regression.

## Details

The gamma.reg fits a Gamma regression with a log-link. The gamma.con fits a Gamma regression with a log link with the intercept only ( glm(y ~ 1, Gamma(log) ) ).

## Value

A list including:

 `deviance` The deviance value. `phi` The dispersion parameter (φ) of the regression. This is necessary if you want to perform an F hypothesis test for the significance of one or more independent variables. `be` The regression coefficient(s). `info` The number of iterations, the deviance and the dispersion parameter.

## Author(s)

Michail Tsagris

R implementation and documentation: Michail Tsagris mtsagris@uoc.gr.

## References

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

` gammaregs, normlog.reg, invgauss.reg `

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11``` ```y <- abs( rnorm(100) ) x <- matrix( rnorm(100 * 2), ncol = 2) mod <- glm(y ~ x, family = Gamma(log) ) res<-summary(mod) ## Not run: res<-gammareg(y, x) ## End(Not run) mod <- glm(y ~ 1, family = Gamma(log) ) res<-summary(mod) res<-gammacon(y) ```

### Example output

```Loading required package: Rcpp