# qpois.reg: Quasi Poisson regression In Rfast: A Collection of Efficient and Extremely Fast R Functions

## Description

Quasi Poisson regression.

## Usage

 ```1 2``` ```qpois.reg(x, y, full = FALSE, tol = 1e-09,maxiters = 100) qpois.regs(x, y, tol = 1e-09, logged = FALSE) ```

## Arguments

 `x` For the "qpois.reg" a matrix with data, the predictor variables. This can be a matrix or a data frame. For the "qpois.regs" this must be a numerical matrix, where each columns denotes a variable. `y` A numerical vector with positive discrete data. `full` If this is FALSE, the coefficients, the deviance and the estimated phi parameter will be returned only. If this is TRUE, more information is returned. `tol` The tolerance value to terminate the Newton-Raphson algorithm. This is set to 10^{-9} by default. `logged` Should the p-values be returned (FALSE) or their logarithm (TRUE)? `maxiters` The maximum number of iterations before the Newton-Raphson is terminated automatically.

## Details

We are using the Newton-Raphson, but unlike R's built-in function "glm" we do no checks and no extra calculations, or whatever. Simply the model, unless the user requests for the Wald tests of the coefficients. The "qpois.regs" is to be used for very many univariate regressions. The "x" is a matrix in this case and the significance of each variable (column of the matrix) is tested.

## Value

For the "prop.reg" a list including: When full is FALSE

 `be` The regression coefficients. `devi` The deviance of the model. `varb` The covariance matrix of the beta coefficients. `phi` The phi parameter, the estimate of dispersion.

When full is TRUE, the additional item is:

 `info` The regression coefficients, their standard error, their Wald test statistic and their p-value.

For the "prop.regs" a two-column matrix with the test statistics (Wald statistic) and the associated p-values (or their loggarithm).

## References

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

``` prop.reg univglms, score.glms, poisson_only ```

## Examples

 ```1 2 3 4 5 6 7 8 9``` ```## Not run: y <- rnbinom(100, 10, 0.6) x <- matrix(rnorm(100*3), ncol = 3) mod1 <- glm(y ~ x, quasipoisson) res<-summary(mod1) res<-qpois.reg(x, y, full = TRUE) res<-qpois.regs(x, y) ## End(Not run) ```

### Example output

```Loading required package: Rcpp