Transform sigma values (log) to original scale

General
,
1

How can I transform the variance (sigma) values in log scale to the original scale in DHGLM models? Specifically in my model: sigma_d13C_Intercept and sigma_d15N_Intercept?

Formula: d13C ~ Sexo * foraging + (1 | a | ID)
sigma ~ Sexo * foraging + (1 | a | ID)
d15N ~ Sexo * foraging + (1 | a | ID)
sigma ~ Sexo * foraging + (1 | a | ID)

Regression Coefficients:
Estimate Est.Error l-95% CI u-95% CI Rhat
d13C_Intercept -15.33 0.10 -15.52 -15.14 1.00
sigma_d13C_Intercept -0.89 0.08 -1.05 -0.73 1.00
d15N_Intercept 17.61 0.26 17.11 18.11 1.00
sigma_d15N_Intercept -0.07 0.10 -0.25 0.13 1.00

2

Say you’ve named your model fit object my_model. Pull the posterior daws with as_draws_df(), and transform the vectors of your choosing within mutate(). To get your \sigma posteriors out of the log scale, you exponentiate with exp().

as_draws_df(my_model) |> 
  dplyr::mutate(sigma_scale = exp(sigma_d13C_Intercept))