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predict()
methods for flexsurv models, in preparation for the upcoming flexsurv release (#317).multi_predict()
is now available for all prediction types for proportional_hazards()
models with the "glmnet"
engine, so newly also for type = "time"
and type = "raw"
(#277, #282).
Random forests with the "aorsf"
engine can now predict survival time, i.e., predict(type = "time")
is now available (#308).
survival_prob_*()
, survival_time_*()
, and hazard_*()
helper functions now all take a parsnip model_fit
object as the main input, instead of an engine fit as was the case for some of them previously (#302).extract_fit_engine()
now works properly for proportional hazards models fitted with the "glmnet"
engine (#266).
multi_predict(type = "survival")
for proportional_hazards(engine = "glmnet")
models: when used with a single penalty
value, this value is now included in the results. It was previously omitted (#267, #282).
proportional_hazards(engine = "glmnet")
models now don’t pretend to be able to deal with sparse matrices when they are not (#291).
Fixed a bug for proportional_hazards(engine = "glmnet")
where prediction didn’t work for a workflow()
with a formula as the preprocessor (#264).
survival_time_coxnet()
and survival_prob_coxnet()
gain a multi
argument to allow multiple values for penalty
(#278, #279).The new eval_time
argument replaces the time
argument for the time points at which to predict survival probability and hazard. The time
argument has been deprecated (#244).
The matrix interface for fitting, fit_xy()
, now works for censored regression models (#225, #234, #247, #251).
Improved error messages throughout the package (#248).
Added the new "aorsf"
engine for rand_forest()
for accelerated oblique random survival forests with the aorsf package (@bcjaeger, #211).
Added the new flexsurvspline
engine for survival_reg()
(@mattwarkentin, #213).
Predictions of type "linear_pred"
for survival_reg(engine = "flexsurv")
are now on the correct scale for distributions where the natural scale and the unrestricted scale of the location parameter are identical, e.g. dist = "lnorm"
(#229).
Predictions of type "linear_pred"
for proportional_hazards(engine = "glmnet")
via multi_predict()
now have the same sign as those via predict()
(#242).
Predictions of survival probability for survival_reg(engine = "flexsurv")
for a single time point are now nested correctly (#254).
Predictions of survival probability for decision_tree(engine = "rpart")
for a single observation now work (#256).
Predictions of type "quantile"
for survival_reg(engine = "survival")
for a single observation now work (#257).
Fixed a bug for printing coxnet
models, i.e., proportional_hazards()
models fitted with the "glmnet"
engine (#249).
Predictions of survival probabilities are now calculated via summary.survfit()
for proportional_hazards()
models with the "survival"
and "glmnet"
engines, bag_tree()
models with the "rpart"
engine, decision_tree()
models with the "partykit"
engines, as well as rand_forest()
models with the "partykit"
engine (#221, #224).
Added internal survfit_summary_*()
helper functions (#216).
For boosted trees with the "mboost"
engine, survival probabilities can now be predicted for time = -Inf
. This is always 1. For time = Inf
this now predicts a survival probability of 0 (#215).
Updated tests on model arguments and update()
methods (#208).
Internal re-organisation of code (#206, 209).
Added a NEWS.md
file to track changes to the package.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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