Package: BTSPAS 2024.11.1
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:
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')) |
Bug tracker:https://github.com/cschwarz-stat-sfu-ca/btspas/issues
Last updated 2 months agofrom:81233b0b34. Checks:OK: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 23 2024 |
R-4.5-linux | OK | Nov 23 2024 |
Exports:expitlogitRunTimeSimplePetersenTestIfPoolTimeStratPetersenDiagError_fitTimeStratPetersenDiagErrorWHChinook_fitTimeStratPetersenDiagErrorWHChinook2_fitTimeStratPetersenDiagErrorWHSteel_fitTimeStratPetersenNonDiagError_fitTimeStratPetersenNonDiagErrorNP_fitTimeStratPetersenNonDiagErrorNPMarkAvail_fitTimeToTargetRunSize
Dependencies:abindactuarbootclicodacolorspacecpp11data.tableexpintfansifarverggforceggplot2gluegridExtragtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigplyrpolyclipR2jagsR2WinBUGSR6RColorBrewerRcppRcppEigenreshape2rjagsrlangscalesstringistringrsystemfontstibbletidyselecttweenrutf8vctrsviridisLitewithr
01 Diagonal model
Rendered froma-Diagonal-model.html.asis
usingR.rsp::asis
on Nov 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.asis
usingR.rsp::asis
on Nov 23 2024.Last update: 2019-12-04
Started: 2019-12-04
03 Non-diagonal model
Rendered fromc-Non-diagonal-model.html.asis
usingR.rsp::asis
on Nov 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.asis
usingR.rsp::asis
on Nov 23 2024.Last update: 2019-12-04
Started: 2019-12-04
05 Bias from incomplete sampling
Rendered frome-Bias-from-incomplete-sampling.html.asis
usingR.rsp::asis
on Nov 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.asis
usingR.rsp::asis
on Nov 23 2024.Last update: 2020-09-05
Started: 2020-09-05