Dunn-Smyth residuals for gllvm model
Calculates Dunn-Smyth residuals for gllvm model.
## S3 method for class 'gllvm' residuals(object, ...)
object |
an object of class 'gllvm'. |
... |
not used. |
Computes Dunn-Smyth residuals (randomized quantile residuals, Dunn and Smyth, 1996) for gllvm model. For the observation Y_{ij} Dunn-Smyth residuals are defined as
r_{ij}=Φ^{-1}(u_{ij}F_{ij}(y_{ij}) + (1-u_{ij})F_{ij}^-(y_{ij})),
where Φ(.) and F_{ij}(.) are the cumulative probability functions of the standard normal distribution, F_{ij}^-(y)) is the limit as F_{ij}(y) is approached from the negative side, and u_{ij} has been generated at random from the standard uniform distribution.
residuals |
matrix of residuals |
linpred |
matrix of linear predictors |
Jenni Niku <jenni.m.e.niku@jyu.fi>
Dunn, P. K., and Smyth, G. K. (1996). Randomized quantile residuals. Journal of Computational and Graphical Statistics, 5, 236-244.
Hui, F. K. C., Taskinen, S., Pledger, S., Foster, S. D., and Warton, D. I. (2015). Model-based approaches to unconstrained ordination. Methods in Ecology and Evolution, 6:399-411.
## Not run: # Load a dataset from the mvabund package data(antTraits) y <- as.matrix(antTraits$abund) # Fit gllvm model fit <- gllvm(y = y, family = poisson()) # residuals res <- residuals(fit) ## End(Not run)
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