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hubEnsembles.Rmd
article now explains how to ensemble
samples using linear_pool()
linear_pool()
supports requesting a subset of component
model sample forecasts when ensembling samples (#144)linear_pool()
supports the specification of the
compound task ID set, so that trajectory samples can be correctly
ensembled (#144)linear_pool()
supports the simplest case of ensembling
samples, where all component samples are collected and returned
(#109)linear_pool()
now uses the argument
derived_task_ids
(derived_tasks
is now
deprecated) (#156)simple_ensemble()
now uses identical()
to
avoid triggering an all.equal.environment()
error. This
error would sometimes occur when providing the agg_fun
argument with a custom function. (#134)hubEnsembles.Rmd
vignette is now an articlelinear_pool()
now properly splits its pools (#128)linear_pool_quantile()
uses internal package functions
only, not Hmisc-utils
functionsall_of()
are updated to avoid throwing
dplyr warnings|>
) is used in place of magrittr
pipe (%>%
)simple_ensemble()
now produces valid distributions for
all weighted medians (#122)weights
argument doesn’t contain weights
dependent on output type ID for PMF and CDF forecasts (#35)map()
and list_rbind()
in conjunction to avoid superseded warnings from purrr (#117).data[[]]
as
appropriate within dplyr functions to avoid warnings (#117)hubEnsembles.Rmd
vignette now better reflects package
capabilities (#29, #113)linear_pool_quantile()
now coerces quantile levels to
numeric to prevent distfromq errors (#58, #63)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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