R/gather-spread.R
gather_sims.Rd
spread_sims()
returns a wide-format data frame. gather_sims()
returns a
long-format data frame. The format matches the format in the tidybayes
spread_draws()
and gather_draws()
functions.
spread_sims(object, nsim = 200, n_sims = deprecated())
gather_sims(object, nsim = 200, n_sims = deprecated())
Output from sdmTMB()
.
The number of simulation draws.
Deprecated: please use nsim
.
A data frame. gather_sims()
returns a long-format data frame:
.iteration
: the sample ID
.variable
: the parameter name
.value
: the parameter sample value
spread_sims()
returns a wide-format data frame:
.iteration
: the sample ID
columns for each parameter with a sample per row
m <- sdmTMB(density ~ 0 + depth_scaled + depth_scaled2,
data = pcod_2011, mesh = pcod_mesh_2011, family = tweedie(),
spatiotemporal = "AR1", time = "year")
head(spread_sims(m, nsim = 10))
#> .iteration depth_scaled depth_scaled2 range phi tweedie_p ar1_rho
#> 1 1 -1.853246 -1.112426 58.93429 13.14827 1.560257 0.9143473
#> 2 2 -1.748585 -1.214495 60.36432 13.03163 1.565090 0.8961658
#> 3 3 -1.667609 -1.243924 71.31742 12.53397 1.557068 0.9085067
#> 4 4 -2.066385 -1.292014 56.91777 13.00500 1.553739 0.8649369
#> 5 5 -1.480440 -1.215773 62.47298 12.62660 1.583245 0.9351527
#> 6 6 -1.850135 -1.251349 50.50230 12.18955 1.560707 0.9031242
#> sigma_O sigma_E
#> 1 Inf 3.064904
#> 2 5.04351e-11 2.438509
#> 3 2.32420e+138 2.361540
#> 4 Inf 2.681585
#> 5 0.00000e+00 2.622512
#> 6 Inf 3.271721
head(gather_sims(m, nsim = 10))
#> .iteration .variable .value
#> 1 1 depth_scaled -1.762974
#> 2 2 depth_scaled -1.813378
#> 3 3 depth_scaled -1.800810
#> 4 4 depth_scaled -1.789012
#> 5 5 depth_scaled -1.772530
#> 6 6 depth_scaled -2.086558
samps <- gather_sims(m, nsim = 1000)
if (require("ggplot2", quietly = TRUE)) {
ggplot(samps, aes(.value)) + geom_histogram() +
facet_wrap(~.variable, scales = "free_x")
}
#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
#> Warning: Removed 338 rows containing non-finite values (stat_bin).