R/MIAmaxent-package.R

In julienvollering/MIAmaxent: A Modular, Integrated Approach to Maximum Entropy Distribution Modeling

#' @keywords internal
#' @details MIAmaxent is intended primarily for maximum entropy
#'   distribution modeling (Phillips et al., 2006; Phillips et al., 2017), and
#'   provides an alternative to the standard methodology for training,
#'   selecting, and using models. The major advantage in this alternative
#'   methodology is greater user control -- in variable transformations, in
#'   variable selection, and in model output. Comparisons also suggest that this
#'   methodology results in simpler models with equally good predictive ability,
#'   and reduces the risk of overfitting (Halvorsen et al., 2016).
#'
#'   The predecessor to this package is the MIA Toolbox, which is described in
#'   detail in Mazzoni et al. (2015).
#'
#' @section Workflow: The diagram below outlines a common workflow for users of
#'   the package. Function names are in red.
#'
#'   \if{html}{\figure{workflow-flowchart.png}{options: width="70\%"
#'   alt="Figure: workflow-flowchart.png"}}
#'   \if{latex}{\figure{workflow-flowchart.pdf}{options: width=12cm}}
#'
#' @references Fithian, W., & Hastie, T. (2013). Finite-sample equivalence in
#'   statistical models for presence-only data. The annals of applied
#'   statistics, 7(4), 1917.
#' @references Halvorsen, R., Mazzoni, S., Bryn, A. & Bakkestuen, V. (2015)
#'   Opportunities for improved distribution modelling practice via a strict
#'   maximum likelihood interpretation of MaxEnt. Ecography, 38, 172-183.
#' @references Halvorsen, R., Mazzoni, S., Dirksen, J.W., Næsset, E., Gobakken,
#'   T. & Ohlson, M. (2016) How important are choice of model selection method
#'   and spatial autocorrelation of presence data for distribution modelling by
#'   MaxEnt? Ecological Modelling, 328, 108-118.
#' @references Mazzoni, S., Halvorsen, R. & Bakkestuen, V. (2015) MIAT: Modular
#'   R-wrappers for flexible implementation of MaxEnt distribution modelling.
#'   Ecological Informatics, 30, 215-221.
#' @references Phillips, S.J., Anderson, R.P., Dudík, M., Schapire, R.E., &
#'   Blair, M.E. (2017). Opening the black box: an open-source release of
#'   Maxent. Ecography, 40(7), 887-893.
#' @references Phillips, S.J., Anderson, R.P. & Schapire, R.E. (2006) Maximum
#'   entropy modeling of species geographic distributions. Ecological Modelling,
#'   190, 231-259.
#' @references Vollering, J., Halvorsen, R., & Mazzoni, S. (2019) The MIAmaxent
#'   R package: Variable transformation and model selection for species
#'   distribution models. Ecology and Evolution, 9(21), 12051–12068.

"_PACKAGE"

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