Plot latent variables from gllvm model
Plots latent variables and their corresponding coefficients (biplot).
## S3 method for class 'gllvm' ordiplot( object, biplot = FALSE, ind.spp = NULL, alpha = 0.5, main = NULL, which.lvs = c(1, 2), predict.region = FALSE, level = 0.95, jitter = FALSE, jitter.amount = 0.2, s.colors = 1, symbols = FALSE, cex.spp = 0.7, spp.colors = "blue", lwd.ellips = 0.5, col.ellips = 4, lty.ellips = 1, ... )
object |
an object of class 'gllvm'. |
biplot |
|
ind.spp |
the number of response variables (usually, species) to include on the biplot. The default is none, or all if |
alpha |
a numeric scalar between 0 and 1 that is used to control the relative scaling of the latent variables and their coefficients, when constructing a biplot. |
main |
main title. |
which.lvs |
indices of two latent variables to be plotted if number of the latent variables is more than 2. A vector with length of two. Defaults to |
predict.region |
logical, if |
level |
level for prediction regions. |
jitter |
if |
jitter.amount |
numeric, positive value indicating an amount of jittering for each point, defaults to 0.2 (jitter range). |
s.colors |
colors for sites |
symbols |
logical, if |
cex.spp |
size of species labels in biplot |
spp.colors |
colors for sites, defaults to |
lwd.ellips |
line width for prediction ellipses. See graphical parameter lwd. |
col.ellips |
colors for prediction ellipses. |
lty.ellips |
line type for prediction ellipses. See graphical parameter lty. |
... |
additional graphical arguments. |
Function constructs a scatter plot of two latent variables, i.e. an ordination plot. If only one latent variable is in the fitted model, latent variables are plotted against their corresponding row indices. The latent variables are labeled using the row index of the response matrix y.
Coefficients related to latent variables are plotted in the same figure with the latent
variables if biplot = TRUE. They are labeled using the column names of y. The number
of latent variable coefficients to be plotted can be controlled by ind.spp. An argument alpha
is used to control the relative scaling of the latent variables and their coefficients.
If alpha = 0.5, the latent variables and their coefficients are on the same scale.
For details for constructing a biplot, see Gabriel (1971).
- If error is occurred when using ordiplot(), try full name of the function ordiplot.gllvm() as functions named 'ordiplot' might be found in other packages as well.
Jenni Niku <jenni.m.e.niku@jyu.fi>, Francis K.C. Hui
Gabriel, K. R. (1971). The biplot graphic display of matrices with application to principal component analysis. Biometrika, 58, 453-467.
#'# Extract subset of the microbial data to be used as an example
data(microbialdata)
y <- microbialdata$Y[, order(colMeans(microbialdata$Y > 0),
decreasing = TRUE)[21:40]]
fit <- gllvm(y, family = poisson())
fit$logL
ordiplot(fit, predict.region = TRUE)
## Not run:
#'## Load a dataset from the mvabund package
data(antTraits)
y <- as.matrix(antTraits$abund)
fit <- gllvm(y, family = poisson())
# Ordination plot:
ordiplot(fit)
# Biplot with 10 species
ordiplot(fit, biplot = TRUE, ind.spp = 10)
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.