summary method for class "hef".

# S3 method for hef
summary(object, ..., params = c("hyper", "pop"),
  which_pop = 1:ncol(object$theta_sim_vals))

Arguments

object

an object of class "hef", a result of a call to hef.

...

Additional arguments passed on to summary.ru.

params

A character scalar.

If params = "hyper" then the posterior samples of all hyperparameter values in \(\phi\) are summarized using summary.ru.

If params = "pop" then only posterior samples of the populations specified in which_pop are summarized.

which_pop

An integer vector. If params = "pop" then which_pop indicates which populations, i.e. which columns of object$theta_sim_vals to summarize, using summary. The default is all populations.

Examples

# Beta-binomial model, rat data rat_res <- hef(model = "beta_binom", data = rat) # Posterior summaries of the hyperparameters alpha and beta summary(rat_res)
#> ru bounding box: #> box vals1 vals2 conv #> a 1.0000000 0.00000000 0.00000000 0 #> b1minus -0.2382163 -0.40313465 -0.03906170 0 #> b2minus -0.2174510 0.05447431 -0.35297539 0 #> b1plus 0.2231876 0.36718411 -0.06551353 0 #> b2plus 0.2512577 0.05665707 0.44459818 0 #> #> estimated probability of acceptance: #> [1] 0.5149331 #> #> sample summary #> alpha beta #> Min. :0.7127 Min. : 4.389 #> 1st Qu.:1.7737 1st Qu.:10.460 #> Median :2.1999 Median :13.093 #> Mean :2.3559 Mean :14.092 #> 3rd Qu.:2.7911 3rd Qu.:16.709 #> Max. :7.2114 Max. :45.562
# Posterior summaries of the binomial probability for rats 1 to 3 summary(rat_res, params = "pop", which_pop = 1:3)
#> p[1] p[2] p[3] #> Min. :0.000287 Min. :0.0003018 Min. :0.0008493 #> 1st Qu.:0.031620 1st Qu.:0.0337496 1st Qu.:0.0342071 #> Median :0.055319 Median :0.0553616 Median :0.0547074 #> Mean :0.063507 Mean :0.0641186 Mean :0.0631619 #> 3rd Qu.:0.086478 3rd Qu.:0.0850060 3rd Qu.:0.0840031 #> Max. :0.227535 Max. :0.2772403 Max. :0.2685869