View source: R/coefplot.manyglm.R

coefplot.manyglm | R Documentation |

A way to plot the coefficients of the covariates of a manyglm object. Modifies code from Niku, Hui and Taskinen's coefplot.gllvm. If you have a large number of terms in your model, consider using which.Xcoef to choose just a few to plot. Default behaviour will try to plot everything, which would be a pretty big figure!

## S3 method for class 'manyglm' coefplot(object, y.label = TRUE, which.Xcoef = NULL, which.Ys = NULL, incl.intercept = FALSE, cex.ylab = 0.5, mfrow = NULL, mar = NULL, ...)

`object` |
A manyglm object |

`y.label` |
Whether all the Y variables should be labelled |

`which.Xcoef` |
Which X covariates should be included in the plot. Defaults to all except intercept. |

`which.Ys` |
Which Y variables should be included in the plot. Defaults to all. |

`incl.intercept` |
Whether the intercept coefficient should be included. |

`cex.ylab` |
A plotting parameter. The default is 0.5. |

`mfrow` |
Plotting parameter |

`mar` |
Plotting parameter |

`...` |
Other plotting parameters |

none

`manyglm`

, `summary.manyglm`

.

## Load the hunting spider data set data(spider) spiddat <- mvabund(spider$abund) #To fit a log-linear model assuming counts are negative binomial: glm.spid <- manyglm(spiddat~., data=spider$x, family="negative.binomial") # A coefplot of soil.dry and bare.sand parameters: coefplot.manyglm(glm.spid, which.Xcoef=2:3) # note which.Xcoef=1 is the intercept

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