testthat, stringr, knitr, rmarkdown, MASS

Simulate and Evaluate Time Series for Environmental Epidemiology
c(person("Sarah", "Koehler", email = "sakoehler7@gmail.com",
role = c("aut")),
person("Brooke", "Anderson", email = "brooke.anderson@colostate.edu",
role = c("aut", "cre")))
Provides functions to create simulated time series of environmental
exposures (e.g., temperature, air pollution) and health outcomes for use in
power analysis and simulation studies in environmental epidemiology. This
package also provides functions to evaluate the results of simulation studies
based on these simulated time series. This work was supported by a grant
from the National Institute of Environmental Health Sciences (R00ES022631) and
a fellowship from the Colorado State University Programs for Research and
Scholarly Excellence.
Sarah Koehler [aut],
Brooke Anderson [aut, cre]

Modelling Framework for the Estimation of Salmonid Abundance
c(
person("Colin", "Millar", role = c("aut", "cre"),
email = "colin.millar@ices.dk"),
person("Rob", "Fryer", role = "aut"),
person("Iain", "Malcolm", role = "aut"),
person("Ross", "Glover", role = "aut"),
person("Marine Scotland Science", role = "cph"))
A set of functions to estimate capture probabilities and
densities from multipass pass removal data.
Colin Millar [aut, cre],
Rob Fryer [aut],
Iain Malcolm [aut],
Ross Glover [aut],
Marine Scotland Science [cph]

Implement European Forestry Dynamics Model
c(
person("Mikko", "Kuronen", email="mikko.kuronen@luke.fi", role=c("aut", "cre"),
comment = c(ORCID = "0000-0002-8089-7895")),
person("Minna", "Räty", email="minna.raty@luke.fi", role="aut",
comment = c(ORCID = "0000-0001-9898-8712")))
An implementation of European Forestry Dynamics Model (EFDM) and
an estimation algorithm for the transition probabilities.
The EFDM is a large-scale forest model that simulates the development of
the forest and estimates volume of wood harvested for any given forested
area. This estimate can be broken down by, for example, species, site
quality, management regime and ownership category.
See Packalen et al. (2015) <doi:10.2788/153990>.
dplyr, ggplot2, gridExtra, knitr, rmarkdown, testthat