Package: PwePred 1.1.2

PwePred: Event/Timeline Prediction Model Based on Piecewise Exponential

Efficient algorithm for estimating piecewise exponential hazard models for right-censored data, and is useful for reliable power calculation, study design, and event/timeline prediction for study monitoring.

Authors:Tianchen Xu [aut, cre]

PwePred_1.1.2.tar.gz
PwePred_1.1.2.zip(r-4.7)PwePred_1.1.2.zip(r-4.6)PwePred_1.1.2.zip(r-4.5)
PwePred_1.1.2.tgz(r-4.6-any)PwePred_1.1.2.tgz(r-4.5-any)
PwePred_1.1.2.tar.gz(r-4.7-any)PwePred_1.1.2.tar.gz(r-4.6-any)
PwePred_1.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
PwePred/json (API)
NEWS

# Install 'PwePred' in R:
install.packages('PwePred', repos = c('https://zjph602xtc.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.00 score 1 scripts 477 downloads 20 exports 12 dependencies

Last updated from:9519ccfadc. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK146
source / vignettesOK175
linux-release-x86_64OK149
macos-release-arm64OK110
macos-oldrel-arm64OK160
windows-develOK113
windows-releaseOK118
windows-oldrelOK113
wasm-releaseOK101

Exports:boot.pwexpmboot.pwexpm_fitcut_datcv.pwexpmcv.pwexpm_fitdpwexpmplot_eventplot_survivalppwexpmppwexpm_conditionalpredict.boot.pwexpmpredict.pwexpmpwexpmpwexpm_fitqpwexpmqpwexpm_conditionalrpwexpmrpwexpm_conditionalsim_followupsimdata

Dependencies:codetoolsdoSNOWfastmatchforeachiteratorslatticeMASSMatrixnlmesegmentedsnowsurvival

Theory Notes

Rendered fromTheory_Notes.Rmdusingknitr::rmarkdownon May 16 2026.

Last update: 2025-04-10
Started: 2025-04-10

Readme and manuals

Help Manual

Help pageTopics
Bootstrap a PWE Model with Formula or Existing Modelboot.pwexpm boot.pwexpm.default boot.pwexpm.pwexpm summary.boot.pwexpm
Bootstrap a PWE Model with Time and Event Vectorsboot.pwexpm_fit
Extract pwexpm Coefficientscoef.pwexpm
The Conditional Piecewise Exponential Distributionppwexpm_conditional qpwexpm_conditional rpwexpm_conditional
Confidence Intervals for Model Parameters in boot.pwexpmconfint.boot.pwexpm
Cut Data before a Specified Timecut_dat
Cross Validate a PWE Model with Formula or Exsiting Modelcv.pwexpm cv.pwexpm.default cv.pwexpm.pwexpm plot.cv.pwexpm
Cross Validate a PWE Model with Time and Event Vectorscv.pwexpm_fit
The Piecewise Exponential Distributiondpwexpm ppwexpm qpwexpm rpwexpm
Plot Cumulative Event Curve with Survival Data or Predicted PWE Modelplot.predict.boot.pwexpm plot.predict.pwexpm plot_event plot_event.default plot_event.predict.boot.pwexpm plot_event.predict.pwexpm
Plot Survival Curve for Survival Data or PWE Modelplot.boot.pwexpm plot.pwexpm plot_survival plot_survival.boot.pwexpm plot_survival.default plot_survival.pwexpm
Predict Events for Piecewise Exponential (PWE) Modelpredict.boot.pwexpm predict.pwexpm summary.predict.boot.pwexpm summary.predict.pwexpm
Piece-wise Exponentail Example Datapwe_data
Piece-wise Exponentail Example Data with 'Abnormal' Tailpwe_data_robust_tail
Fit a PWE Model with Formulapwexpm summary.pwexpm
Fit a PWE model with Time and Event Vectorspwexpm_fit
OS Curves from Ruppert (2020)ruppert_ipd
Estimate Follow-up Time and Number of Events by Simulationsim_followup
Simulate Survival Datasimdata