Extract estimated parameters from fitted model.

get_pars(fitted_model, conf_int = 0.05)

Arguments

fitted_model

The fitted model returned as an rstan object from the call to zoid

conf_int

Parameter controlling confidence intervals calculated, defaults to 0.05 for 95% intervals

Value

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()

Examples

# \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 2.9e-05 seconds
#> Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.29 seconds.
#> Chain 1: Adjust your expectations accordingly!
#> Chain 1: 
#> Chain 1: 
#> Chain 1: Iteration:    1 / 2000 [  0%]  (Warmup)
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#> Chain 1: 
#> Chain 1:  Elapsed Time: 0.107425 seconds (Warm-up)
#> Chain 1:                0.105028 seconds (Sampling)
#> Chain 1:                0.212453 seconds (Total)
#> Chain 1: 
#> 
#> SAMPLING FOR MODEL 'dirichregmod' NOW (CHAIN 2).
#> Chain 2: 
#> Chain 2: Gradient evaluation took 2.5e-05 seconds
#> Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 0.25 seconds.
#> Chain 2: Adjust your expectations accordingly!
#> Chain 2: 
#> Chain 2: 
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#> Chain 2: 
#> Chain 2:  Elapsed Time: 0.101962 seconds (Warm-up)
#> Chain 2:                0.103542 seconds (Sampling)
#> Chain 2:                0.205504 seconds (Total)
#> Chain 2: 
#> 
#> SAMPLING FOR MODEL 'dirichregmod' NOW (CHAIN 3).
#> Chain 3: 
#> Chain 3: Gradient evaluation took 2.4e-05 seconds
#> Chain 3: 1000 transitions using 10 leapfrog steps per transition would take 0.24 seconds.
#> Chain 3: Adjust your expectations accordingly!
#> Chain 3: 
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#> Chain 3: Iteration: 2000 / 2000 [100%]  (Sampling)
#> Chain 3: 
#> Chain 3:  Elapsed Time: 0.10487 seconds (Warm-up)
#> Chain 3:                0.109294 seconds (Sampling)
#> Chain 3:                0.214164 seconds (Total)
#> Chain 3: 
p_hat <- get_pars(fit)
# }