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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in conjunction to avoid superseded warnings from purrr (#117).data[[]] as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.