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, ...)
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.
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.
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. 10.1111/j.1368-423X.2004.00125.x
The summary methods for bridge and bridge_list objects automatically invoke this function, see bridge-methods.