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tidychangepoint (version 1.0.0)

BMDL: Bayesian Maximum Descriptive Length

Description

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

Usage

BMDL(object, ...)

# S3 method for default BMDL(object, ...)

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

Value

A double vector of length 1

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.

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: HQC(), MBIC(), MDL(), SIC()

Examples

Run this code
# Compute the BMDL
BMDL(fit_nhpp(DataCPSim, tau = NULL))
BMDL(fit_nhpp(DataCPSim, tau = c(365, 830)))

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