Package: nowcastr 0.2.1

Mathias Leroy

nowcastr: Nowcasting with Chain-Ladder Method

Nowcasting using the Chain-Ladder method. Supports both non-cumulative delay-based estimation and model-based completeness fitting (e.g., using logistic or Gompertz curves) to predict final counts from partially reported data.

Authors:Mathias Leroy [aut, cre], Finlay Campbell [aut]

nowcastr_0.2.1.tar.gz
nowcastr_0.2.1.zip(r-4.7)nowcastr_0.2.1.zip(r-4.6)nowcastr_0.2.1.zip(r-4.5)
nowcastr_0.2.1.tgz(r-4.6-any)nowcastr_0.2.1.tgz(r-4.5-any)
nowcastr_0.2.1.tar.gz(r-4.7-any)nowcastr_0.2.1.tar.gz(r-4.6-any)
nowcastr_0.2.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
nowcastr/json (API)

# Install 'nowcastr' in R:
install.packages('nowcastr', repos = c('https://whocov.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/whocov/nowcastr/issues

Pkgdown/docs site:https://whocov.github.io

Datasets:

On CRAN:

Conda:

quarto

5.20 score 2 stars 5 scripts 450 downloads 18 exports 29 dependencies

Last updated from:2196bb5e26. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK215
source / vignettesOK232
linux-release-x86_64OK209
macos-release-arm64OK156
macos-oldrel-arm64OK126
windows-develOK136
windows-releaseOK132
windows-oldrelOK154
wasm-releaseOK148

Exports:%>%calculate_retro_scorefill_future_reported_valuesgenerate_test_datanowcast_clnowcast_evalnowcast_eval_resultsnowcast_explorenowcast_resultsplot_delaysplot_nc_inputplot_nowcastplot_nowcast_evalplot_nowcast_eval_by_delayplot_nowcast_eval_detailrm_repeated_valuestbl_models_statstheme_nowcastr

Dependencies:clicpp11dplyrfarvergenericsggplot2gluegtableisobandlabelinglifecyclemagrittrpillarpkgconfigpurrrR6RColorBrewerrlangS7scalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr

Evaluate accuracy
Run evaluation | Plots | Plot aggregated indicators | Plot one indicator by delay | Plot raw values, for one delay | Examples: Evaluate Scenarios | Example 1: Vary fill_future_reported_values | Example 2: Vary max_reportunits
Rendered fromeval.qmdusingquarto::html

Last update: 2026-07-03
Started: 2026-03-31

Getting started
Setup | Data Structure | Workflow | 1. Visualize Input Data | 2. Prepare Data (Optional) | 3. Run Nowcast | 4. Explore Results | How It Works | Other Utility Functions | Calculate Retro Scores of input data | Remove repeated values
Rendered fromnowcastr.qmdusingquarto::html

Last update: 2026-05-15
Started: 2026-03-30