View source: R/ordinate.jsdgam.R
| ordinate.jsdgam | R Documentation |
Plot an ordination of latent variables and their factor loadings from
jsdgam models
ordinate(object, ...)
## S3 method for class 'jsdgam'
ordinate(
object,
which_lvs = c(1, 2),
biplot = TRUE,
alpha = 0.5,
label_sites = TRUE,
...
)
object |
|
... |
ignored |
which_lvs |
A |
biplot |
|
alpha |
A proportional numeric scalar between |
label_sites |
|
This function constructs a two-dimensional scatterplot in ordination space.
The chosen latent variables are first re-rotated using singular value
decomposition, so that the first plotted latent variable does not have to
be the first latent variable that was estimated in the original model.
Posterior median estimates of the variables and the species' loadings on
these variables are then used to construct the resulting plot. Some attempt
at de-cluttering the resulting plot is made by using geom_label_repel()
and geom_text_repel from the ggrepel package, but if there are many
sites and/or species then some labels may be removed automatically. Note
that you can typically get better, more readable plot layouts if you also
have the ggarrow and ggpp packages installed
An ggplot object
Nicholas J Clark
jsdgam(), residual_cor()
## Not run:
# Fit a JSDGAM to the portal_data captures
mod <- jsdgam(
formula = captures ~
# Fixed effects of NDVI and mintemp, row effect as a GP of time
ndvi_ma12:series + mintemp:series + gp(time, k = 15),
factor_formula = ~ -1,
data = portal_data,
unit = time,
species = series,
family = poisson(),
n_lv = 2,
silent = 2,
chains = 2
)
# Plot a residual ordination biplot
ordinate(
mod,
alpha = 0.7
)
# Compare to a residual correlation plot
plot(
residual_cor(mod)
)
## End(Not run)
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