Extract estimated parameters from fitted model.
get_pars(fitted_model, conf_int = 0.05)The fitted model returned as an rstan object from the call to zoid
Parameter controlling confidence intervals calculated, defaults to 0.05 for 95% intervals
A list containing the posterior summaries of estimated parameters. At minimum,
this will include p (the estimated proportions) and betas (the predicted values in
transformed space). For models with overdispersion, an extra
element phi will also be returned, summarizing overdispersion. For predictions
in normal space, see get_fitted()
# \donttest{
y <- matrix(c(3.77, 6.63, 2.60, 0.9, 1.44, 0.66, 2.10, 3.57, 1.33),
nrow = 3, byrow = TRUE
)
# fit a model with no covariates
fit <- fit_zoid(data_matrix = y)
#>
#> SAMPLING FOR MODEL 'dirichregmod' NOW (CHAIN 1).
#> Chain 1:
#> Chain 1: Gradient evaluation took 2.3e-05 seconds
#> Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.23 seconds.
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#> Chain 1:
#>
#> SAMPLING FOR MODEL 'dirichregmod' NOW (CHAIN 2).
#> Chain 2:
#> Chain 2: Gradient evaluation took 2.2e-05 seconds
#> Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 0.22 seconds.
#> Chain 2: Adjust your expectations accordingly!
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#> Chain 2:
#>
#> SAMPLING FOR MODEL 'dirichregmod' NOW (CHAIN 3).
#> Chain 3:
#> Chain 3: Gradient evaluation took 2e-05 seconds
#> Chain 3: 1000 transitions using 10 leapfrog steps per transition would take 0.2 seconds.
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#> Chain 3:
p_hat <- get_pars(fit)
# }