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 |
| 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-release: BTSPAS_2020.1.1.zip, r-oldrel: BTSPAS_2020.1.1.zip |
| macOS binaries: | r-release: BTSPAS_2020.1.1.tgz, r-oldrel: BTSPAS_2020.1.1.tgz |
| Old sources: | BTSPAS archive |
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