hdMTD 0.1.2
New
- Accessor functions for “MTD”:
pj()
, p0()
,
lambdas()
, lags()
, Lambda()
,
states()
, and transitP()
. See
?MTD-accessors
.
- Accessor functions for “MTDest”:
pj()
,
p0()
, lambdas()
, lags()
,
S()
and states()
. See
?MTD-accessors
.
- Accessor functions for “hdMTD”:
S()
and
lags()
. See ?MTD-accessors
.
- Methods for “MTD” and “MTDest” objects: added
print()
,
summary()
, coef()
, logLik()
and
probs()
. For compact inspection of lag sets, state space,
mixture weights and more. See ?MTD-methods
and
?MTDest-methods
.
- Methods for “hdMTD” objects: added
print()
and
summary()
for compact inspection of lag selection results.
See ?hdMTD-methods
.
- Coercion: new
as.MTD()
to rebuild an “MTD” object from
an “MTDest” fit.
Changes
probs()
is now a S3 generic with methods for “MTD” and
“MTDest”. Returns one-step-ahead predictive probabilities either for
specific contexts (context=
) or from sample rows
(newdata=
). If neither is supplied, it returns the full
global transition matrix (transitP(object)
for
MTD
; transitP(as.MTD(object))
for
MTDest
).
- Renamed the sample-based estimator
probs(X, S, ...)
to
empirical_probs(X, S, ...)
to avoid ambiguity:
empirical_probs()
estimates transition probabilities from
data, while probs()
returns predictive probabilities from
model/fit objects.
Fixes
- Replaced
any(is.na(X))
with anyNA(X)
in
checkSample()
for efficiency and clarity.
Package cleanup
- Removed unused datasets (
raindata
,
sleepscoring
, testChains
).
- Updated examples to use simulated data (via
perfectSample()
) instead of the removed
testChains
dataset.
- Internal helpers marked
@keywords internal
so they no
longer appear in help(package="hdMTD")
.
hdMTD 0.1.1
- Relicensed the package from MIT to GPL-3.
- Removed an unintended
README.md
file from the package
source.