parallel, doParallel, foreach, Matrix, coda, statmod, RMark,
Brobdingnag, mvtnorm, graphics, methods, stats, utils, prodlim,
sp, raster, doRNG

Traditional and spatial capture-mark-recapture analysis with
multiple non-invasive marks. The models implemented in 'multimark' combine
encounter history data arising from two different non-invasive "marks",
such as images of left-sided and right-sided pelage patterns of bilaterally
asymmetrical species, to estimate abundance and related demographic
parameters while accounting for imperfect detection. Bayesian models are
specified using simple formulae and fitted using Markov chain Monte Carlo.
Addressing deficiencies in currently available software, 'multimark' also
provides a user-friendly interface for performing Bayesian multimodel
inference using non-spatial or spatial capture-recapture data consisting of a single
conventional mark or multiple non-invasive marks. See McClintock (2015) <doi:10.1002/ece3.1676> and Maronde et al. (2020) <doi:10.1002/ece3.6990>.

Jose Ameijeiras-Alonso [aut,cre],
Rosa M. Crujeiras [aut],
Alberto Rodríguez-Casal [aut],
The R Core Team 1996-2012 [ctb,cph] (C function 'BinDist2' obtained from package 'stats'),
The R Foundation 2005 [ctb,cph] (C function 'BinDist2' obtained from package 'stats')
Different examples and methods for testing (including different proposals described in Ameijeiras-Alonso et al., 2016 <arXiv:1609.05188>) and exploring (including the mode tree, mode forest and SiZer) the number of modes using nonparametric techniques.

Different examples and methods for testing (including different proposals described in Ameijeiras-Alonso et al., 2018 <DOI:10.1007/s11749-018-0611-5>) and exploring (including the mode tree, mode forest and SiZer) the number of modes using nonparametric techniques.

Different examples and methods for testing (including different proposals described in Ameijeiras-Alonso et al., 2019 <DOI:10.1007/s11749-018-0611-5>) and exploring (including the mode tree, mode forest and SiZer) the number of modes using nonparametric techniques <DOI:10.18637/jss.v097.i09>.