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.

Version: 2020.1.1
Imports: actuar, coda, data.table, ggplot2, ggforce, graphics, grDevices, gridExtra, plyr, reshape2, R2jags, splines, stats, utils
Suggests: R.rsp
Published: 2019-12-04
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: http://www.stat.sfu.ca/~cschwarz/Consulting/Trinity/Phase2
NeedsCompilation: no
SystemRequirements: JAGS
Citation: BTSPAS citation info
Materials: README NEWS
CRAN checks: BTSPAS results

Downloads:

Reference manual: BTSPAS.pdf
Vignettes: 01 Diagonal model
02 Diagonal model with multiple ages
03 Non-diagonal model
04 Non-diagonal with fall-back model
05 Bias from incomplete sampling
Package source: BTSPAS_2020.1.1.tar.gz
Windows binaries: r-devel: BTSPAS_2020.1.1.zip, r-devel-gcc8: BTSPAS_2020.1.1.zip, r-release: BTSPAS_2020.1.1.zip, r-oldrel: BTSPAS_2020.1.1.zip
OS X binaries: r-release: BTSPAS_2020.1.1.tgz, r-oldrel: BTSPAS_2020.1.1.tgz
Old sources: BTSPAS archive

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