error_measures: Error Measures for Estimated Marginal Likelihood

Description Usage Arguments Details Value Note Author(s) References See Also

Description

Computes error measures for estimated marginal likelihood.

Usage

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error_measures(bridge_object, ...)

## S3 method for class 'bridge'
error_measures(bridge_object, ...)

## S3 method for class 'bridge_list'
error_measures(bridge_object, na.rm = TRUE, ...)

Arguments

bridge_object

an object of class "bridge" or "bridge_list" as returned from bridge_sampler.

...

additional arguments (currently ignored).

na.rm

a logical indicating whether missing values in logml estimates should be removed. Ignored for the bridge method.

Details

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.

Value

If bridge_object is of class "bridge" and has been obtained with method = "normal" and repetitions = 1, returns a list with components:

If bridge_object is of class "bridge_list", returns a list with components:

Note

For examples, see bridge_sampler and the accompanying vignettes:
vignette("bridgesampling_example_jags")
vignette("bridgesampling_example_stan")

Author(s)

Quentin F. Gronau

References

Fruehwirth-Schnatter, S. (2004). Estimating marginal likelihoods for mixture and Markov switching models using bridge sampling techniques. The Econometrics Journal, 7, 143-167. doi: 10.1111/j.1368-423X.2004.00125.x

See Also

The summary methods for bridge and bridge_list objects automatically invoke this function, see bridge-methods.


bridgesampling documentation built on April 16, 2021, 9:07 a.m.