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Bayesian Maximum Descriptive Length

BMDL.Rd

Generic function to compute the Bayesian Maximum Descriptive Length for a changepoint detection model.

Usage

BMDL(object, ...)

# Default S3 method
BMDL(object, ...)

# S3 method for class 'nhpp'
BMDL(object, ...)

Arguments

object

any object from which a log-likelihood value, or a contribution to a log-likelihood value, can be extracted.

...

some methods for this generic function require additional arguments.

Value

A double vector of length 1

Details

Currently, the BMDL function is only defined for the NHPP model (see fit_nhpp()). Given a changepoint set \(\tau\), the BMDL is: $$ BMDL(\tau, NHPP(y | \hat{\theta}_\tau) = P_{MDL}(\tau) - 2 \ln{ L_{NHPP}(y | \hat{\theta}_\tau) } - 2 \ln{ g(\hat{\theta}_\tau) } $$ where \(P_{MDL}(\tau)\) is the MDL() penalty.

See also

Other penalty-functions: MBIC(), MDL()

Examples

# Compute the BMDL
BMDL(fit_nhpp(DataCPSim, tau = NULL))
#> [1] 1453.906
BMDL(fit_nhpp(DataCPSim, tau = c(365, 830)))
#> [1] 1235.144