Extract inverse metric (inverse mass matrix) after MCMC

Extract the inverse metric (inverse mass matrix) for each MCMC chain.

The inverse metric is defined over the unconstrained parameter space, so its entries do not necessarily correspond one-to-one with the constrained parameters declared in the parameters block (some transformations from constrained to unconstrained change dimensions). See Examples for a way to add names to the entries of the inverse metric when the model has parameters that change dimensions when unconstrained.

Usage

inv_metric(matrix = TRUE)

Arguments

matrix

(logical) If a diagonal metric was used, setting matrix = FALSE returns a list containing just the diagonals of the matrices instead of the full matrices. Setting matrix = FALSE has no effect for dense metrics.

Value

A list of length equal to the number of MCMC chains. See the matrix argument for details.

See also

CmdStanMCMC

Examples

# \dontrun{
stan_file <- write_stan_file("
  parameters {
    simplex[3] theta;
  }
  model {
    theta ~ dirichlet(rep_vector(1, 3));
  }
")
mod <- cmdstan_model(stan_file)

# use higher output precision so the simplex remains valid after CSV rounding
fit <- mod$sample(chains = 1, sig_figs = 10)
#> Running MCMC with 1 chain...
#> 
#> Chain 1 Iteration:    1 / 2000 [  0%]  (Warmup) 
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#> Chain 1 finished in 0.0 seconds.

# even though theta has 3 elements, the inverse metric is 2x2 because the
# simplex constraint reduces the dimension. we set `matrix = FALSE` in this case
# because we estimated a diagonal matrix (we didn't set `metric = "dense_e"`
# when fitting the model), so we can just look at the diagonal elements
inv_metric <- fit$inv_metric(matrix = FALSE)

# the list has 1 element since we only ran 1 chain for simplicity
print(inv_metric)
#> $`1`
#> [1] 1.57846 1.67959
#> 

# get names of unconstrained parameters and add them to the inverse metric
# (unconstrain_draws() requires compiling additional methods)
inv_metric_names <- posterior::variables(fit$unconstrain_draws())
inv_metric <- lapply(inv_metric, stats::setNames, nm = inv_metric_names)

# the names will be theta[1] and theta[2], but these are not the same as
# the first two elements of the constrained theta in the Stan program
inv_metric
#> $`1`
#> theta[1] theta[2] 
#>  1.57846  1.67959 
#> 
# }