| summary.metafrontier | R Documentation |
Computes group-level summaries of technical efficiency (TE),
technology gap ratio (TGR), and metafrontier efficiency (TE*),
full coefficient tables for each group frontier (including
variance parameters and, for BC92 panels, eta, all with
standard errors where a Hessian is available), the metafrontier
coefficient table (with Murphy-Topel corrected standard errors
where applicable), and a per-stage convergence table.
## S3 method for class 'metafrontier'
summary(object, ...)
object |
a |
... |
additional arguments (currently unused). |
An object of class "summary.metafrontier": a list
with components
the matched call of the original fit
estimation method ("sfa" or "dea")
metafrontier type ("deterministic" or
"stochastic")
character vector of group labels
named vector of observation counts (total and per group)
named list of coefficient matrices, one per
group, with columns Estimate, Std. Error,
z value, and Pr(>|z|) where standard errors are
available (empty list for DEA fits)
metafrontier coefficient matrix in the same
format, or NULL for DEA fits
data frame of TGR statistics by group, as
returned by tgr_summary
data frame with mean TE, mean TGR, and mean TE* by group
named vector of group log-likelihoods, or
NULL
Stage 2 log-likelihood of the stochastic
metafrontier, or NULL
data frame with columns stage,
code, and converged recording the optimiser
status of each estimation stage, or NULL if
unavailable; see check_convergence
sim <- simulate_metafrontier(n_groups = 2, n_per_group = 50, seed = 42)
fit <- metafrontier(log_y ~ log_x1 + log_x2, data = sim$data,
group = "group", meta_type = "stochastic")
s <- summary(fit)
print(s)
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