Description Usage Arguments Details Author(s) References See Also Examples

Five plots (selectable by which) are currently available: a plot of residuals against linear predictors of fitted values, a Normal Q-Q plot of residuals with a simulated point-wise 95% confidence interval envelope, residuals against row index and column index and scale location plot.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ```
## S3 method for class 'gllvm'
plot(
x,
which = 1:5,
caption = c("Residuals vs linear predictors", "Normal Q-Q", "Residuals vs row",
"Residuals vs column", "Scale-Location"),
var.colors = NULL,
add.smooth = TRUE,
envelopes = TRUE,
reps = 150,
envelope.col = c("blue", "lightblue"),
n.plot = NULL,
...
)
``` |

`x` |
an object of class 'gllvm'. |

`which` |
if a subset of the plots is required, specify a subset of the numbers 1:5, see caption below. |

`caption` |
captions to appear above the plots. |

`var.colors` |
colors for responses, vector with length of number of response variables or 1. Defaults to NULL, when different responses have different colors. |

`add.smooth` |
logical indicating if a smoother should be added. |

`envelopes` |
logical, indicating if simulated point-wise confidence interval envelope will be added to Q-Q plot, defaults to |

`reps` |
number of replications when simulating confidence envelopes for normal Q-Q plot |

`envelope.col` |
colors for envelopes, vector with length of two |

`n.plot` |
number of species (response variables) to be plotted. Defaults to |

`...` |
additional graphical arguments. |

plot.gllvm is used for model diagnostics. Dunn-Smyth residuals (randomized quantile residuals) (Dunn and Smyth, 1996) are used in plots. Colors indicate different species.

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.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | ```
## Not run:
## Load a dataset from the mvabund package
data(antTraits)
y <- as.matrix(antTraits$abund)
# Fit gllvm model with Poisson family
fit <- gllvm(y, family = poisson())
# Plot residuals
plot(fit, mfrow = c(3,2))
\donttest{
# Fit gllvm model with negative binomial family
fitnb <- gllvm(y = y, family = "negative.binomial")
# Plot residuals
plot(fitnb, mfrow = c(3,2))
# Plot only two first plots
plot(fitnb, which = 1:2, mfrow = c(1,2))
}
## End(Not run)
``` |

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