assess a neural estimator
assess(
estimators,
parameters,
Z,
estimator_names = NULL,
parameter_names = NULL,
use_gpu = TRUE,
verbose = TRUE
)a list of two data frames: runtimes contains the
total time taken for each estimator, while df is a long-form
data frame with columns:
"estimator"; the name of the estimator
"parameter"; the name of the parameter
"truth"; the true value of the parameter
"estimate"; the estimated value of the parameter
"m"; the sample size (number of iid replicates)
"k"; the index of the parameter vector in the test set
"j"; the index of the data set
a neural estimator (or a list of neural estimators)
true parameters, stored as a \(d\times K\) matrix, where \(d\) is the dimension of the parameter vector and \(K\) is the number of sampled parameter vectors
data simulated conditionally on the parameters. If length(Z) > K, the parameter matrix will be recycled by horizontal concatenation as parameters = parameters[, rep(1:K, J)], where J = length(Z) / K
list of names of the estimators (sensible defaults provided)
list of names of the parameters (sensible defaults provided)
a boolean indicating whether to use the GPU if it is available (default true)
a boolean indicating whether information should be printed to the console
risk(), rmse(), bias(), plotestimates(), and plotdistribution() for computing various empirical diagnostics and visualisations from an object returned by assess()