Convergence Checks for an emc Object

Runs a series of convergence checks, prints statistics to the console, and makes traceplots of the worst converged parameter per selection.

Usage

# S3 method for class 'emc'
check(
  emc,
  selection = c("mu", "sigma2", "alpha"),
  digits = 3,
  plot_worst = TRUE,
  ...
)

check(emc, ...)

Arguments

emc: An emc object
selection: A Character vector. Indicates which parameter types to check (e.g., alpha, mu, sigma2, correlation).
digits: Integer. How many digits to round the ESS and Rhat to in the plots
plot_worst: Boolean. If TRUE also plots the chain plots for the worst parameter
...: Optional arguments that can be passed to get_pars or plot.default (see par())

Value

a list with the statistics for the worst converged parameter per selection

Details

Note that the Rhat is calculated by doubling the number of chains by first splitting chains into first and second half, so it also a test of stationarity.

Efficiency of sampling is indicated by the effective sample size (ESS) (from the coda R package). Full range of possible samples manipulations described in get_pars.

Examples

check(samples_LNR)
#> Iterations:
#>      preburn burn adapt sample
#> [1,]       0    0     0     50
#> [2,]       0    0     0     50
#> [3,]       0    0     0     50
#> 
#>  mu 
#>            m   m_lMd       s      t0
#> Rhat   1.066   1.017   1.035   1.006
#> ESS  150.000 178.000 150.000 143.000
#> 
#>  sigma2 
#>            m   m_lMd       s      t0
#> Rhat   1.032   1.003   1.003   0.993
#> ESS  133.000 115.000 150.000 150.000
#> 
#>  alpha highest Rhat : bd6t 
#>            m   m_lMd       s      t0
#> Rhat   1.039   0.995   1.004   1.029
#> ESS  140.000 150.000 600.000 158.000