Plot MLE vs MCMC marginal standard deviations for each parameter
Source:R/utils.R
plot_uncertainties.Rd
Plot MLE vs MCMC marginal standard deviations for each parameter
Arguments
- fit
A fitted object returned by
sample_admb
- log
Whether to plot the axes in log space (default TRUE).
- plot
Whether to plot it or not.
Value
Invisibly returns data.frame with parameter name (row) and estimated uncertainties for each method (columns).
Details
It can be helpful to compare uncertainty estimates between the two paradigms. This plots the marginal posterior standard deviation vs the frequentist standard error estimated from the .cor file. Large differences often indicate issues with one estimation method.
Examples
fit <- readRDS(system.file('examples', 'fit.RDS', package='adnuts'))
x <- plot_uncertainties(fit, plot=FALSE)
head(x)
#> par sd.post sd.mle
#> a a 0.2028936 0.15547
#> b b 0.9112519 0.70394