Package: BTSPAS 2026.3.1

BTSPAS: Bayesian Time-Stratified Population Analysis

Provides advanced Bayesian methods to estimate abundance and run-timing from temporally-stratified Petersen mark-recapture experiments. Methods include hierarchical modelling of the capture probabilities and spline smoothing of the daily run size. Theory described in Bonner and Schwarz (2011) <doi:10.1111/j.1541-0420.2011.01599.x>.

Authors:Carl J Schwarz [aut, cre], Simon J Bonner [aut]

BTSPAS_2026.3.1.tar.gz
BTSPAS_2026.3.1.zip(r-4.7)BTSPAS_2026.3.1.zip(r-4.6)BTSPAS_2026.3.1.zip(r-4.5)
BTSPAS_2026.3.1.tgz(r-4.6-any)BTSPAS_2026.3.1.tgz(r-4.5-any)
BTSPAS_2026.3.1.tar.gz(r-4.7-any)BTSPAS_2026.3.1.tar.gz(r-4.6-any)
BTSPAS_2026.3.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
BTSPAS/json (API)

# Install 'BTSPAS' in R:
install.packages('BTSPAS', repos = c('https://cschwarz-stat-sfu-ca.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/cschwarz-stat-sfu-ca/btspas/issues

Uses libs:
  • jags– Just Another Gibbs Sampler for Bayesian MCMC
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

jagscpp

4.94 score 1 stars 29 scripts 752 downloads 13 exports 44 dependencies

Last updated from:db6eaa3aa9. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK169
source / vignettesOK204
linux-release-x86_64OK192
macos-release-arm64OK182
macos-oldrel-arm64OK192
windows-develOK108
windows-releaseOK121
windows-oldrelOK110
wasm-releaseOK119

Exports:expitlogitRunTimeSimplePetersenTestIfPoolTimeStratPetersenDiagError_fitTimeStratPetersenDiagErrorWHChinook_fitTimeStratPetersenDiagErrorWHChinook2_fitTimeStratPetersenDiagErrorWHSteel_fitTimeStratPetersenNonDiagError_fitTimeStratPetersenNonDiagErrorNP_fitTimeStratPetersenNonDiagErrorNPMarkAvail_fitTimeToTargetRunSize

Dependencies:abindactuarbackportsbase64encbootcheckmateclicodacpp11data.tableexpintfarverggforceggplot2gluegridExtragtableisobandjsonlitelabelinglatticelifecyclemagrittrMASSplyrpolyclipR2jagsR2WinBUGSR6RColorBrewerRcppreshape2rjagsrlangS7scalesstringistringrsystemfontstidyselecttweenrvctrsviridisLitewithr

06 Interpolating run earlier and later
Rendered fromf-Interpolating-run-earlier-and-later.html.asisusingR.rsp::asis

Last update: 2020-08-09
Started: 2020-08-09

01 Diagonal model
Rendered froma-Diagonal-model.html.asisusingR.rsp::asis

Last update: 2019-12-04
Started: 2019-12-04

02 Diagonal model with multiple ages
Rendered fromb-Diagonal-model-with-multiple-ages.html.asisusingR.rsp::asis

Last update: 2019-12-04
Started: 2019-12-04

03 Non-diagonal model
Rendered fromc-Non-diagonal-model.html.asisusingR.rsp::asis

Last update: 2019-12-04
Started: 2019-12-04

04 Non-diagonal with fall-back model
Rendered fromd-Non-diagonal-with-fall-back-model.html.asisusingR.rsp::asis

Last update: 2019-12-04
Started: 2019-12-04

05 Bias from incomplete sampling
Rendered frome-Bias-from-incomplete-sampling.html.asisusingR.rsp::asis

Last update: 2019-12-04
Started: 2019-12-04