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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>.
Version: | 2024.5.9 |
Imports: | actuar, coda, data.table, ggplot2, ggforce, graphics, grDevices, gridExtra, plyr, reshape2, R2jags, scales, splines, stats, utils |
Suggests: | R.rsp |
Published: | 2024-05-10 |
DOI: | 10.32614/CRAN.package.BTSPAS |
Author: | Carl J Schwarz and Simon J Bonner |
Maintainer: | Carl J Schwarz <cschwarz.stat.sfu.ca at gmail.com> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
URL: | https://github.com/cschwarz-stat-sfu-ca/BTSPAS |
NeedsCompilation: | no |
SystemRequirements: | JAGS |
Citation: | BTSPAS citation info |
Materials: | README NEWS |
CRAN checks: | BTSPAS results |
Package source: | BTSPAS_2024.5.9.tar.gz |
Windows binaries: | r-devel: BTSPAS_2024.5.9.zip, r-release: BTSPAS_2024.5.9.zip, r-oldrel: BTSPAS_2024.5.9.zip |
macOS binaries: | r-release (arm64): BTSPAS_2024.5.9.tgz, r-oldrel (arm64): BTSPAS_2024.5.9.tgz, r-release (x86_64): BTSPAS_2024.5.9.tgz, r-oldrel (x86_64): BTSPAS_2024.5.9.tgz |
Old sources: | BTSPAS archive |
Reverse imports: | Petersen |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.