BMDL | R Documentation |
Generic function to compute the Bayesian Maximum Descriptive Length for a changepoint detection model.
BMDL(object, ...)
## Default S3 method:
BMDL(object, ...)
## S3 method for class 'nhpp'
BMDL(object, ...)
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. |
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.
A double
vector of length 1
Other penalty-functions:
HQC()
,
MBIC()
,
MDL()
,
SIC()
# Compute the BMDL
BMDL(fit_nhpp(DataCPSim, tau = NULL))
BMDL(fit_nhpp(DataCPSim, tau = c(365, 830)))
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