Computes error measures for estimated marginal likelihood.
error_measures(bridge_object, ...)# S3 method for bridge
error_measures(bridge_object, ...)
# S3 method for bridge_list
error_measures(bridge_object, na.rm = TRUE, ...)
If bridge_object is of class "bridge" and has been obtained with method = "normal" and repetitions = 1, returns a list with components:
re2: approximate relative mean-squared error for marginal likelihood estimate.
cv: approximate coefficient of variation for marginal likelihood estimate (assumes that bridge estimate is unbiased).
percentage: approximate percentage error of marginal likelihood estimate.
If bridge_object is of class "bridge_list", returns a list with components:
min: minimum of the log marginal likelihood estimates.
max: maximum of the log marginal likelihood estimates.
IQR: interquartile range of the log marginal likelihood estimates.
an object of class "bridge" or "bridge_list" as returned from bridge_sampler.
additional arguments (currently ignored).
a logical indicating whether missing values in logml estimates should be removed. Ignored for the bridge method.
Quentin F. Gronau
Computes error measures for marginal likelihood bridge sampling estimates. The approximate errors for a bridge_object of class "bridge" that has been obtained with method = "normal" and repetitions = 1 are based on Fruehwirth-Schnatter (2004).
Not applicable in case the object of class "bridge" has been obtained with method = "warp3" and repetitions = 1.
To assess the uncertainty of the estimate in this case, it is recommended to run the "warp3" procedure multiple times.
Fruehwirth-Schnatter, S. (2004). Estimating marginal likelihoods for mixture and Markov switching models using bridge sampling techniques. The Econometrics Journal, 7, 143-167. tools:::Rd_expr_doi("10.1111/j.1368-423X.2004.00125.x")
The summary methods for bridge and bridge_list objects automatically invoke this function, see bridge-methods.