assess: assess a neural estimator

In NeuralEstimators: Likelihood-Free Parameter Estimation using Neural Networks

assess a neural estimator

Description

assess a neural estimator

Usage

assess(
  estimators,
  parameters,
  Z,
  estimator_names = NULL,
  parameter_names = NULL,
  use_gpu = TRUE,
  verbose = TRUE
)

Arguments

estimators	a list of (neural) estimators
parameters	true parameters, stored as a pxK matrix, where p is the number of parameters in the statistical model and K is the number of sampled parameter vectors
Z	data simulated conditionally on the parameters. If Z contains more data sets than parameter vectors, the parameter matrix will be recycled by horizontal concatenation.
estimator_names	list of names of the estimators (sensible defaults provided)
parameter_names	list of names of the parameters (sensible defaults provided)
use_gpu	a boolean indicating whether to use the GPU if it is available (default true)
verbose	a boolean indicating whether information should be printed to the console

Value

a list of two data frames: runtimes, contains the total time taken for each estimator, while estimates 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

See Also

risk(), rmse(), bias(), plotestimates(), and plotdistribution() for computing various empirical diagnostics and visualisations based on an assessment object

NeuralEstimators documentation built on Nov. 3, 2024, 9:07 a.m.