germany_covid19_hosp and make new package data named
covid19_data which extends through August 2022.baselinenowcast.reporting_triangle() and
baselinenowcast.data.frame to
estimate_uncertainty() and
sample_nowcasts().estimate_delay() that is
larger than the number of rows in the reporting triangle.ref_time_aggregator tests,
skipping those tests on CRAN with skip_on_cran(), and
setting a seed in a stochastic test that could fail intermittently
(#488).pkgdown article in vignettes/articles/ so that
it is no longer built on CRAN. The article is rendered when the
pkgdown site is built in CI (#488).as_forecast_sample() and
as_forecast_point() S3 methods for
baselinenowcast_df objects, enabling direct conversion of
probabilistic or point nowcasts to scoringutils forecast
objects for scoring against the latest observed counts (#418).
baselinenowcast_df objects now carry a logical
nowcast column flagging the right-truncated reference dates
that were actually nowcast (as opposed to fully observed), and the
converters use it to score only those dates.R/reporting_triangle-class.R and
R/baselinenowcast_df-class.R; per-caller helpers in the
file that calls them) and remove R/validate.R. Generalise
assert_rep_tri_class() with an arg_name
argument and use it to replace duplicated inline class checks in
truncate_to_quantile(), truncate_to_delay(),
and the reporting triangle getters and methods (#300).reporting_triangle and reviser vintages
formats via as_reviser_vintages() and
as_reporting_triangle.tbl_pubdate(), enabling use of
reviser’s vintage analysis and state space nowcasting methods alongside
baselinenowcast’s nowcasting functionality (#429).truncate_to_date(), a date-based wrapper around
truncate_to_row() that drops rows with reference dates
after a given cutoff (#447).This is the first stable release providing core functionality for
producing probabilistic or point nowcasts from a dataframe with incident
case counts indexed by reference dates and report dates. It supports
doing so across multiple strata, either through creating
reporting_triangle objects for each strata and nowcasting
independently, or nowcasting directly from a dataframe containing
multiple strata. The reporting_triangle object allows users
to specify the unit of the delay, and provides helpful
print and summary S3 methods, as well as
functionality to truncate to a specific delay or a percentile of the
observed delays. A paper validating and evaluating the performance of
the methods is available at https://wellcomeopenresearch.org/articles/10-614/v1.
fill_triangle() has been removed. Use
estimate_and_apply_delay() instead, which now supports
optional delay estimation via the delay_pmf parameter
(#334).fill_triangles() has been removed. Use
estimate_and_apply_delays() instead (#334).truncate_triangle() to
truncate_to_row() and truncate_triangles() to
truncate_to_rows() to clarify that these functions truncate
by row count and distinguish them from other truncation utilities such
as truncate_to_quantile() and
truncate_to_delay() (#336).as_reporting_triangle and
baselinenowcast workflow in the vignette which walks
through a nowcasting example applied to syndromic surveillance data in
the U.S.preprocess parameter to
estimate_delay() to control handling of negative values in
reporting triangles. Set to preprocess_negative_values by
default to redistribute negative values to earlier delays, or set to
NULL to preserve negative PMF entries. This allows the
method to work with reporting corrections that result in net downward
adjustments at specific delays (#278).preprocess_negative_values() function to allow
users to manually handle negative values in reporting triangles by
redistributing them to earlier delays (#278).baselinenowcast.data.frame() method which ingests
a data.frame with one or more strata to nowcast and returns a
baselinenowcast_df object.reporting_triangle and
ChainLadder triangle formats via as_ChainLadder_triangle()
and as_reporting_triangle.triangle(), enabling use of
ChainLadder’s mature claims reserving methods alongside
baselinenowcast’s nowcasting functionality.baselinenowcast.reporting_triangle() method which
ingests a reporting_triangle object and produces a
baselinenowcast_df object which is a data.frame with
nowcasts and associated metadata.as_reporting_triangle() S3 method which ingests a
data.frame or matrix and returns a reporting_triangle
object, which will be used as an input to the eventual
baselinenowcast() function.baselinenowcast to nowcast cases of a specific syndromic
surveillance definition.estimate_uncertainty to take in an error model
function, an aggregator function for aggregating across reference times,
and an aggregator function for aggregating across delays.baselinenowcast() wrapper function.n are specified
for the delay estimate.estimate_dispersion() function to transform the “target”
dataset across reference dates.replace_lower_right_with_NA()
with generate_triangle().structure vector must not be greater than the number of
columns.