# residuals.manyglm: Residuals for MANYGLM, MANYANY, GLM1PATH Fits In mvabund: Statistical Methods for Analysing Multivariate Abundance Data

## Description

Obtains Dunn-Smyth residuals from a fitted `manyglm`, `manyany` or `glm1path` object.

## Usage

 ```1 2``` ```## S3 method for class 'manyglm' residuals(object, ...) ```

## Arguments

 `object` a fitted object of class inheriting from `"manyglm"`. `...` further arguments passed to or from other methods.

## Details

`residuals.manyglm` computes Randomised Quantile or “Dunn-Smyth" residuals (Dunn & Smyth 1996) for a `manyglm` object. If the fitted model is correct then Dunn-Smyth residuals are standard normal in distribution.

Similar functions have been written to compute Dunn-Smyth residuals from `manyany` and `glm1path` objects.

Note that for discrete data, Dunn-Smyth residuals involve random number generation, and will not return identical results on replicate runs. Hence it is worth calling this function multiple times to get a sense for whether your interpretation of results holds up under replication.

## Value

A matrix of Dunn-Smyth residuals.

## Author(s)

David Warton <[email protected]>.

## References

Dunn, P.K., & Smyth, G.K. (1996). Randomized quantile residuals. Journal of Computational and Graphical Statistics 5, 236-244.

`manyglm`, `manyany`, `glm1path`, `plot.manyglm`.
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20``` ```data(spider) spiddat <- mvabund(spider\$abund) X <- spider\$x ## obtain residuals for Poisson regression of the spider data, and doing a qqplot: glmP.spid <- manyglm(spiddat~X, family="poisson") resP <- residuals(glmP.spid) qqnorm(resP) qqline(resP,col="red") #clear departure from normality. ## try again using negative binomial regression: glmNB.spid <- manyglm(spiddat~X, family="negative.binomial") resNB <- residuals(glmNB.spid) qqnorm(resNB) qqline(resNB,col="red") #that looks a lot more promising. #note that you could construct a similar plot directly from the manyglm object using plot(glmNB.spid, which=2) ```