Miscellaneous Functions for Data Cleaning and Analysis
Provides functions needed for data cleaning and
formatting and forms data cleaning and wrangling backend for the
following packages: 'ggstatsplot', 'groupedstats',
'pairwiseComparisons', and 'statsExpressions' packages.
crayon (>= 1.3.4), dplyr (>= 0.8.3), broomExtra, rlang (>=
0.4.2), rstudioapi, tibble (>= 2.0.1), tidyr (>= 1.0.0),
zeallot
ggplot2, knitr, rmarkdown, spelling, testthat

Provides functions needed for data cleaning and
formatting and forms data cleaning and wrangling backend for the
following packages: 'ggstatsplot', 'groupedstats',
'pairwiseComparisons', and 'statsExpressions'.
broomExtra, crayon, dplyr (>= 0.8.3), forcats, rlang (>=
0.4.2), rstudioapi, tibble (>= 2.0.1), tidyr (>= 1.0.0),
zeallot
ggplot2, knitr, parameters, rmarkdown, spelling, testthat

broomExtra, crayon, dplyr (>= 0.8.3), forcats, rlang (>=
0.4.2), rstudioapi, tibble (>= 2.1.3), tidyr (>= 1.0.0),
zeallot

Provides functions needed for data cleaning and
formatting and forms data cleaning and wrangling backend for the
following packages: 'broomExtra', 'ggstatsplot', 'groupedstats',
'pairwiseComparisons', 'statsExpressions', and 'tidyBF'.
crayon, dplyr, forcats, magrittr, rlang, rstudioapi, tibble,
tidyr, zeallot

crayon, dplyr, magrittr, rlang, rstudioapi, tibble, tidyr,
zeallot

ggplot2, knitr, rmarkdown, parameters, spelling, testthat

dplyr, magrittr, rlang, tibble, tidyr, zeallot
ggplot2, rmarkdown, parameters, spelling, testthat

crayon, dplyr, magrittr, rlang, tibble, tidyr, zeallot

Provides functions needed for data cleaning and
formatting and forms data cleaning and wrangling backend for the
following packages: 'ggstatsplot', 'pairwiseComparisons',
'statsExpressions', and 'tidyBF'.

Provides functions needed for data cleaning and
formatting and forms data cleaning and wrangling backend for the
following packages: 'ggstatsplot', 'pairwiseComparisons', and
'statsExpressions'.

Fits Integral Projection Models Using an Expression Based
Framework
c(
person(given = "Sam",
family = "Levin",
role = c("aut", "cre"),
email = "levisc8@gmail.com",
comment = c(ORCID = "0000-0002-3289-9925")),
person(given = "Aldo",
family = "Compagnoni",
email = "aldo.compagnoni@idiv.de",
role = "aut"),
person(given = "Dylan",
family = "Childs",
email = "d.childs@sheffield.ac.uk",
role = "aut"),
person(given = "Sanne",
family = "Evers",
email = "sanne.evers@idiv.de",
role = "aut"),
person(given = "Roberto",
family = "Salguero-Gomez",
email = "rob.salguero@zoo.ox.ac.uk",
role = "aut"),
person(given = "Tiffany",
family = "Knight",
email = "tiffany.knight@idiv.de",
role = "aut"))
Flexibly implements Integral Projection Models using an expression
based framework. This will not abstract away the model selection process,
but it will make sure you get everything after that correct. It handles density
dependence and environmental stochasticity, with a couple of options for
implementing the latter. In addition, provides functions to avoid unintentional
eviction of individuals from models. Additionally, provides model diagnostic tools,
plotting functionality, stochastic/deterministic simulations, and analysis tools.
Integral projection models are described in depth by Easterling et al. (2000)
<doi:10.1890/0012-9658(2000)081[0694:SSSAAN]2.0.CO;2>, Merow et al. (2013)
<doi:10.1111/2041-210X.12146>, Rees et al. (2014) <doi:10.1111/1365-2656.12178>,
and Metcalf et al. (2015) <doi:10.1111/2041-210X.12405>.
Williams et al. (2012) <doi:10.1890/11-2147.1> discuss the problem of
unintentional eviction.
knitr, lme4, mvtnorm, rmarkdown, roxygen2, spelling,
testthat, covr
graphics, grDevices, magrittr, methods, purrr (>= 0.3.0),
rlang (>= 0.3.0), stats, utils, Rcpp
Sam Levin [aut, cre] (<https://orcid.org/0000-0002-3289-9925>),
Aldo Compagnoni [aut],
Dylan Childs [aut],
Sanne Evers [aut],
Roberto Salguero-Gomez [aut],
Tiffany Knight [aut]