From the output of the function fit_trend()
(or read_bugs()
), this
function checks if the estimation of all parameters of one (or several)
BUGS model has converged. This diagnostic is performed by comparing the
Rhat
value of each parameter to a threshold
(default is 1.1
). If some
Rhat
values are greater than this threshold (no convergence), a message
listing problematic models is displayed.
Arguments
- data
a named
list
of BUGS outputs. The output offit_trend()
orread_bugs()
.- threshold
a
numeric
.
Examples
## Load Garamba raw dataset ----
file_path <- system.file("extdata", "garamba_survey.csv",
package = "popbayes")
garamba <- read.csv(file = file_path)
## Create temporary folder ----
temp_path <- tempdir()
## Format dataset ----
garamba_formatted <- popbayes::format_data(
data = garamba,
path = temp_path,
field_method = "field_method",
pref_field_method = "pref_field_method",
conversion_A2G = "conversion_A2G",
rmax = "rmax")
#> ✔ Detecting 10 count series.
## Select one serie ----
a_buselaphus <- popbayes::filter_series(garamba_formatted,
location = "Garamba",
species = "Alcelaphus buselaphus")
#> ✔ Found 1 series with "Alcelaphus buselaphus" and "Garamba".
# \donttest{
## Fit population trends (requires JAGS) ----
a_buselaphus_mod <- popbayes::fit_trend(a_buselaphus, path = temp_path)
#> Compiling data graph
#> Resolving undeclared variables
#> Allocating nodes
#> Initializing
#> Reading data back into data table
#> Compiling model graph
#> Resolving undeclared variables
#> Allocating nodes
#> Graph information:
#> Observed stochastic nodes: 15
#> Unobserved stochastic nodes: 15
#> Total graph size: 227
#>
#> Initializing model
#>
## Check for convergence ----
popbayes::diagnostic(a_buselaphus_mod)
#> ✔ All models have converged.
# }