Extract site- or species-level summary statistics for predictions from a jsdmStanFit
model
jsdm_statsummary.Rd
This function extracts the predicted Y values for within the models and then calculates summary statistics for each simulated community. The default is to sum all the predicted scores for each site.
Usage
jsdm_statsummary(
object,
species = NULL,
sites = NULL,
summary_stat = "sum",
post_type = "linpred",
calc_over = "site",
simplify = TRUE,
draw_ids = NULL,
ndraws = NULL,
...
)
Arguments
- object
A
jsdmStanFit
model object- species
Which species to include in the summary statistic, by default all
- sites
Which sites to include in the summary statistic, by default all
- summary_stat
The summary statistic to be used, by default
sum
but any function can be used.- post_type
The type of posterior prediction to be used, either
"linpred"
forposterior_linpred.jsdmStanFit()
or"predict"
forposterior_predict.jsdmStanFit()
- calc_over
Whether to calculate the summary statistic by site or species, by default
species
- simplify
Whether to simplify the output into a matrix, by default
TRUE
- draw_ids
The IDs of the draws to be used, as a numeric vector
- ndraws
Number of draws, by default the number of samples in the posterior. Will be sampled randomly from the chains if fewer than the number of samples.
- ...
Arguments passed to the posterior prediction function
Value
If simplify = TRUE
then a matrix where each row is a draw and each
column is either a site (if calc_over = "site"
) or a species (if
calc_over = "species"
).
Examples
if (FALSE) { # \dontrun{
# First simulate data and fit the jsdmStan model:
gllvm_data <- gllvm_sim_data(
N = 100, S = 9, D = 2,
family = "bernoulli"
)
gllvm_fit <- stan_gllvm(dat_list = gllvm_data, family = "bernoulli")
# The default is to return a matrix:
jsdm_statsummary(gllvm_fit)
# The above returns the linear predictor, while we may want to get the posterior
# prediction instead:
jsdm_statsummary(gllvm_fit, post_type = "predict")
# This can be limited to a specific set of species and/or sites:
jsdm_statsummary(gllvm_fit, species = 1:5, sites = seq(5, 95, 10))
} # }