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rolling_origin_pals(): a genuine out-of-sample
(rolling-origin) evaluation, re-estimating the model at each of a set of
origin dates from strictly earlier events and scoring predictions on the
following holdout window. Complements the one-step-ahead (“marching
forward”) criterion that estimate_pals() minimizes, in
which every event’s own location contributes to the single fitted
parameter vector.bootstrap_pals() gains a block argument
for a block bootstrap (block = "year", or a user-supplied
grouping vector) that preserves within-block temporal/actor dependence,
as an alternative to the default i.i.d. event bootstrap.pool_rubin() quick-start example,
which errored with “unused arguments” when called with
q =/u = (the function’s arguments are named
estimates/variances); updated install
instructions to lead with CRAN and to add
build_vignettes = TRUE to the GitHub install example, so
vignette("palsr") is available after following the
README.pal_events(),
estimate_pals() (one- and four-parameter models),
project_pal() / project_pals(),
predict_event_locations(), and
pal_distance().bootstrap_pals() and
Rubin’s Rules pooling with pool_rubin().nigeria_sim and
simulate_conflict_events().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.
Health stats visible at Monitor.