Python 2.7.x or Python 3.2.x-3.4.x, NumPy (Python
scientific computing package)

Reconstruct population counts, fertility, mortality and
migration rates of human populations of the recent past.
Implements the Bayesian hierarchical model described by
Wheldon, Raftery Clark and Gerland (see:
http://www.csss.washington.edu/Papers/wp108.pdf) for
simultaneously estimating age-specific population counts,
fertility rates, mortality rates and net international
migration flows, at the national level.

Implements the Bayesian hierarchical model described by Wheldon, Raftery Clark and Gerland (see: http://www.csss.washington.edu/Papers/wp108.pdf) for simultaneously estimating age-specific population counts, fertility rates, mortality rates and net international migration flows, at the national level.

Reconstruct Human Populations of the Recent Past
Implements the Bayesian hierarchical model described by Wheldon, Raftery, Clark and Gerland (see: http://www.csss.washington.edu/Papers/wp108.pdf) for simultaneously estimating age-specific population counts, fertility rates, mortality rates and net international migration flows, at the national level.

Implements the Bayesian hierarchical model described by Wheldon, Raftery, Clark and Gerland (see: <doi:10.1080/01621459.2012.737729>) for simultaneously estimating age-specific population counts, fertility rates, mortality rates and net international migration flows, at the national level.

Bayesian Model to Estimate Population Trends from Counts Series
c(
person(
given   = "Nicolas",
family  = "Casajus",
email   = "nicolas.casajus@fondationbiodiversite.fr",
role    = c("aut", "cre", "cph"),
comment = c(ORCID = "0000-0002-5537-5294")),
person(
given   = "Roger",
family  = "Pradel",
email   = "roger.pradel@cefe.cnrs.fr",
role    = "aut",
comment = c(ORCID = "0000-0002-2684-9251")))
Infers the trends of one or several animal populations over time
from series of counts. It does so by accounting for count precision
(provided or inferred based on expert knowledge, e.g. guesstimates),
smoothing the population rate of increase over time, and accounting for the
maximum demographic potential of species. Inference is carried out in a
Bayesian framework. This work is part of the FRB-CESAB working group
AfroBioDrivers
<https://www.fondationbiodiversite.fr/en/the-frb-in-action/programs-and-projects/le-cesab/afrobiodrivers/>.
graphics, grDevices, R2jags, stats, usethis
Nicolas Casajus [aut, cre, cph]
(<https://orcid.org/0000-0002-5537-5294>),
Roger Pradel [aut] (<https://orcid.org/0000-0002-2684-9251>)