Plots covariate coefficients and their confidence intervals.

# S3 method for gllvm coefplot( object, y.label = TRUE, which.Xcoef = NULL, order = TRUE, cex.ylab = 0.5, mfrow = NULL, mar = c(4, 6, 2, 1), xlim.list = NULL, ... )

object | an object of class 'gllvm'. |
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y.label | logical, if |

which.Xcoef | vector indicating which covariate coefficients will be plotted. Can be vector of covariate names or numbers. Default is |

order | logical, whether or not coefficients are ordered, defaults to |

cex.ylab | the magnification to be used for axis annotation relative to the current setting of cex. |

mfrow | same as |

mar | vector of length 4, which defines the margin sizes: |

xlim.list | list of vectors with length of two to define the intervals for an x axis in each covariate plot. Defaults to NULL when the interval is defined by the range of point estimates and confidence intervals |

... | additional graphical arguments. |

Jenni Niku <jenni.m.e.niku@jyu.fi>, Francis K.C. Hui, Sara Taskinen

# Extract subset of the microbial data to be used as an example data(microbialdata) X <- microbialdata$Xenv y <- microbialdata$Y[, order(colMeans(microbialdata$Y > 0), decreasing = TRUE)[21:40]] fit <- gllvm(y, X, formula = ~ pH + Phosp, family = poisson()) coefplot(fit)if (FALSE) { ## Load a dataset from the mvabund package data(antTraits) y <- as.matrix(antTraits$abund) X <- as.matrix(antTraits$env) # Fit model with environmental covariates fit <- gllvm(y, X, formula = ~ Bare.ground + Shrub.cover, family = poisson()) coefplot.gllvm(fit) # Fit model with all environmental covariates fitx <- gllvm(y, X, family = "negative.binomial") coefplot(fitx, mfrow = c(3,2)) coefplot(fitx, which.Xcoef = 1:2) # Fit gllvm model with environmental and trait covariates TR <- antTraits$traits fitT <- gllvm(y = y, X = X, TR = TR, family = "negative.binomial") coefplot(fitT) }