The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

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>.

Version: 2024.11.1
Imports: actuar, coda, data.table, ggplot2, ggforce, graphics, grDevices, gridExtra, plyr, reshape2, R2jags, scales, splines, stats, utils
Suggests: R.rsp
Published: 2024-10-23
DOI: 10.32614/CRAN.package.BTSPAS
Author: Carl J Schwarz [aut, cre], Simon J Bonner [aut]
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

Documentation:

Reference manual: BTSPAS.pdf
Vignettes: 01 Diagonal model (source)
02 Diagonal model with multiple ages (source)
03 Non-diagonal model (source)
04 Non-diagonal with fall-back model (source)
05 Bias from incomplete sampling (source)
06 Interpolating run earlier and later (source)

Downloads:

Package source: BTSPAS_2024.11.1.tar.gz
Windows binaries: r-devel: BTSPAS_2024.11.1.zip, r-release: BTSPAS_2024.11.1.zip, r-oldrel: BTSPAS_2024.11.1.zip
macOS binaries: r-release (arm64): BTSPAS_2024.11.1.tgz, r-oldrel (arm64): BTSPAS_2024.11.1.tgz, r-release (x86_64): BTSPAS_2024.11.1.tgz, r-oldrel (x86_64): BTSPAS_2024.11.1.tgz
Old sources: BTSPAS archive

Reverse dependencies:

Reverse imports: Petersen

Linking:

Please use the canonical form https://CRAN.R-project.org/package=BTSPAS to link to this page.

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.
Health stats visible at Monitor.