- Settings previously stored as
model$alpha,
model$symmetric, model$integrate,
model$scorecast, model$lr,
model$Csat and model$KI are now collected in
model$args.
forecast moved from Imports to
Depends, so it is attached together with
conformalForecast.
acmcp() now accepts ma_method = "CSS" for
faster MA scorecaster fitting at longer forecast horizons, while
retaining "CSS-ML" as the default, and reports successful
scorecasts in scorecast_times.
- New unit-test suite covering all four conformal methods,
cvforecast(), update(), and the evaluation
functions.
Bug fixes
- Corrected lower-tail calibration scores in
scp() and
acp(), ensuring that the infinite finite-sample correction
is retained with the correct sign.
kess = TRUE now requires a continuous quantile
estimator (quantiletype = 4:9); an informative error is
returned for discontinuous quantile estimators.
acmcp() no longer fits MA models before its recursive
scorecaster inputs are available.
update() now works on pid(),
acmcp() and acp(symmetric = TRUE) objects, and
resumes from the last computed step instead of recomputing the whole
history.
update() now replays stored arguments, preserves
forecasts at all frequencies, validates new data and external
regressors, and handles failed final model fits. External regressors are
retained by pid() and acmcp(), enabling
external-regressor updates for all four conformal methods.
pid() and acmcp() can be called with their
documented defaults.
print() and summary() no longer repeat the
cross-validation header.
cvforecast() no longer warns about arguments
legitimately passed to forecastfun, and survives a failing
final model fit.
cp_times is reported per forecast horizon.
coverage() and width() accept
x, LOWER and UPPER through
..., and require a single level.
lagmatrix() handles lags larger than the number of
rows.
- Clearer error from
scp() and acp() when
ncal is too large.
Documentation
- The pkgdown site renders mathematics again
(
math-rendering: mathjax).
- Corrected the documented return classes, the
Winkler
measure name, the lagmatrix() error message, and several
typos.
- Expanded the vignette with the
conformal() interface,
incremental updates, external regressors, clearer method descriptions,
and updated ggplot2 calls.
- New
vignette("update"), on extending a fitted conformal
pipeline with newly arrived observations instead of refitting it from
scratch.
- The introductory vignette now documents
conformal(),
and describes each method, its key formula and its tuning arguments in
more detail.
- The pkgdown site indexes both vignettes under “Articles”.
- Help examples now cover raw inputs to
coverage() and
width() and cpforecast accuracy, and use fixed
random seeds for reproducibility.
- Changed accuracy.default to use S3 methods
Initial features
- Provides implementations of the main conformal prediction methods:
scp (split conformal prediction)
acp (adaptive conformal prediction)
pid (conformal PID control method)
acmcp (autocorrelated multi-step conformal
prediction).
- Includes utility functions to compute coverage rates and interval
widths for evaluating predictive performance.