Package: seroreconstruct 1.1.5

seroreconstruct: Reconstructing Antibody Dynamics to Estimate the Risk of Influenza Virus Infection

A Bayesian framework for inferring influenza infection status from serial antibody measurements. Jointly estimates season-specific infection probabilities, antibody boosting and waning after infection, and baseline hemagglutination inhibition (HAI) titer distributions via Markov chain Monte Carlo (MCMC). Supports multi-season analysis and subgroup comparisons via a group_by interface. See Tsang et al. (2022) <doi:10.1038/s41467-022-29310-8> for methodological details.

Authors:Tim Tsang [aut, cre]

seroreconstruct_1.1.5.tar.gz
seroreconstruct_1.1.5.zip(r-4.7-x86_64)seroreconstruct_1.1.5.zip(r-4.7-arm64)seroreconstruct_1.1.5.zip(r-4.6-x86_64)seroreconstruct_1.1.5.zip(r-4.6-arm64)seroreconstruct_1.1.5.zip(r-4.5-x86_64)
seroreconstruct_1.1.5.tgz(r-4.6-x86_64)seroreconstruct_1.1.5.tgz(r-4.6-arm64)seroreconstruct_1.1.5.tgz(r-4.5-x86_64)seroreconstruct_1.1.5.tgz(r-4.5-arm64)
seroreconstruct_1.1.5.tar.gz(r-4.7-arm64)seroreconstruct_1.1.5.tar.gz(r-4.7-x86_64)seroreconstruct_1.1.5.tar.gz(r-4.6-arm64)seroreconstruct_1.1.5.tar.gz(r-4.6-x86_64)
seroreconstruct_1.1.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
seroreconstruct/json (API)

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

Bug tracker:https://github.com/timktsang/seroreconstruct/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • flu_activity - Example of flu activity data
  • inputdata - Example of input data
  • para1 - Example of parameter vector for the main model
  • para2 - Example of parameter vector for the baseline HAI titer for the main model

On CRAN:

Conda:

openblascpp

4.48 score 5 scripts 248 downloads 10 exports 3 dependencies

Last updated from:5bb6441eaa. Checks:15 OK. Indexed: yes.

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linux-devel-arm64OK154
linux-devel-x86_64OK152
source / vignettesOK236
linux-release-arm64OK145
linux-release-x86_64OK154
macos-release-arm64OK151
macos-release-x86_64OK381
macos-oldrel-arm64OK119
macos-oldrel-x86_64OK302
windows-devel-arm64OK373
windows-devel-x86_64OK193
windows-release-arm64OK373
windows-release-x86_64OK143
windows-oldrel-x86_64OK150
wasm-releaseOK110

Exports:output_model_estimateplot_boostingplot_diagnosticsplot_infection_probplot_trajectoryplot_waningsero_reconstructsimulate_datatable_infectionstable_parameters

Dependencies:RcppRcppArmadilloRcppParallel

Getting Started with seroreconstruct
Overview | Input data | Fitting the model | Viewing results | Visualization | MCMC diagnostics | Antibody trajectories | Boosting and waning | Infection probabilities | Tables | Subgroup analysis | Joint model with shared parameters | Simulation | Citation
Rendered fromintroduction.Rmdusingknitr::rmarkdown

Last update: 2026-03-30
Started: 2026-03-23

Statistical Methodology
Model overview | Notation | Antibody dynamics model | Measurement error model | Infection risk model | Prior distributions | MCMC implementation | Convergence diagnostics | Recommendations for production analyses | Parameter layout | Shared parameter models | References
Rendered frommethodology.Rmdusingknitr::rmarkdown

Last update: 2026-03-23
Started: 2026-03-23