Extract values of used or fitted history parameter mixed_state

A short-cut for history_parameter(object, "mixed_state", ...).

Usage

history_mixed_state(
  object,
  summary = TRUE,
  probs = c(0.055, 0.945),
  includePopulationLevel = TRUE
)

Arguments

object

An object of class cumhist

summary

Whether summary statistics should be returned instead of raw sample values. Defaults to TRUE

probs

The percentiles used to compute summary, defaults to 89% credible interval.

includePopulationLevel

Logical, for pooled random effect only. Whether to include population mean as a separate "_population" level, default to TRUE.

Value

A single value, if fixed value was used. A vector or a tibble, depending on the option used (single intercept, independent or random intercepts), and whether summary was requested.

Examples

# \donttest{
br_fit <- fit_cumhist(br_singleblock, state="State", duration="Duration")
#> 
#> SAMPLING FOR MODEL 'historylm' NOW (CHAIN 1).
#> Chain 1: 
#> Chain 1: Gradient evaluation took 0 seconds
#> Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
#> Chain 1: Adjust your expectations accordingly!
#> Chain 1: 
#> Chain 1: 
#> Chain 1: Iteration:    1 / 2000 [  0%]  (Warmup)
#> Chain 1: Iteration:  200 / 2000 [ 10%]  (Warmup)
#> Chain 1: Iteration:  400 / 2000 [ 20%]  (Warmup)
#> Chain 1: Iteration:  600 / 2000 [ 30%]  (Warmup)
#> Chain 1: Iteration:  800 / 2000 [ 40%]  (Warmup)
#> Chain 1: Iteration: 1000 / 2000 [ 50%]  (Warmup)
#> Chain 1: Iteration: 1001 / 2000 [ 50%]  (Sampling)
#> Chain 1: Iteration: 1200 / 2000 [ 60%]  (Sampling)
#> Chain 1: Iteration: 1400 / 2000 [ 70%]  (Sampling)
#> Chain 1: Iteration: 1600 / 2000 [ 80%]  (Sampling)
#> Chain 1: Iteration: 1800 / 2000 [ 90%]  (Sampling)
#> Chain 1: Iteration: 2000 / 2000 [100%]  (Sampling)
#> Chain 1: 
#> Chain 1:  Elapsed Time: 5.096 seconds (Warm-up)
#> Chain 1:                5.428 seconds (Sampling)
#> Chain 1:                10.524 seconds (Total)
#> Chain 1: 
history_tau(br_fit)
#> # A tibble: 1 x 3
#>   Estimate `5.5%` `94.5%`
#>      <dbl>  <dbl>   <dbl>
#> 1    0.982  0.786    1.20
# }