Package: BTSPAS 2024.11.1

Carl J Schwarz

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_2024.11.1.tar.gz
BTSPAS_2024.11.1.tar.gz(r-4.5-noble)BTSPAS_2024.11.1.tar.gz(r-4.4-noble)
BTSPAS_2024.11.1.tgz(r-4.4-emscripten)BTSPAS_2024.11.1.tgz(r-4.3-emscripten)
BTSPAS.pdf |BTSPAS.html✨
BTSPAS/json (API)
NEWS

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

Peer review:

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

jagscpp

5.18 score 2 stars 1 packages 28 scripts 848 downloads 13 exports 50 dependencies

Last updated 2 months agofrom:81233b0b34. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKDec 23 2024
R-4.5-linuxOKDec 23 2024

Exports:expitlogitRunTimeSimplePetersenTestIfPoolTimeStratPetersenDiagError_fitTimeStratPetersenDiagErrorWHChinook_fitTimeStratPetersenDiagErrorWHChinook2_fitTimeStratPetersenDiagErrorWHSteel_fitTimeStratPetersenNonDiagError_fitTimeStratPetersenNonDiagErrorNP_fitTimeStratPetersenNonDiagErrorNPMarkAvail_fitTimeToTargetRunSize

Dependencies:abindactuarbootclicodacolorspacecpp11data.tableexpintfansifarverggforceggplot2gluegridExtragtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigplyrpolyclipR2jagsR2WinBUGSR6RColorBrewerRcppRcppEigenreshape2rjagsrlangscalesstringistringrsystemfontstibbletidyselecttweenrutf8vctrsviridisLitewithr

01 Diagonal model

Rendered froma-Diagonal-model.html.asisusingR.rsp::asison Dec 23 2024.

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::asison Dec 23 2024.

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

03 Non-diagonal model

Rendered fromc-Non-diagonal-model.html.asisusingR.rsp::asison Dec 23 2024.

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::asison Dec 23 2024.

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

05 Bias from incomplete sampling

Rendered frome-Bias-from-incomplete-sampling.html.asisusingR.rsp::asison Dec 23 2024.

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

06 Interpolating run earlier and later

Rendered fromf-Interpolating-run-earlier-and-later.html.asisusingR.rsp::asison Dec 23 2024.

Last update: 2020-09-05
Started: 2020-09-05