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NEWS.md

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* quiet option added to top-level functions performing selection
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* readData() automatically removes duplicates when two or more presences/absences fall in the same cell
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* readData() discards presence locations with missing EV data
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* formula argument to selectEV() function, to specifiy starting point for selection
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* formula argument to selectEV() function, to specify starting point for selection
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* plotFOP() smoother changed to loess from exponentially weighted moving average
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* plotFOP() plots data density behind FOP values
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* plotFOP() returns plot data invisibly

R/MIAmaxent.R

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#' @references Mazzoni, S., Halvorsen, R. & Bakkestuen, V. (2015) MIAT: Modular
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#' R-wrappers for flexible implementation of MaxEnt distribution modelling.
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#' Ecological Informatics, 30, 215-221.
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#' @references Phillips, S.J., Anderson, R.P., Dudik, M., Schapire, R.E., &
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#' @references Phillips, S.J., Anderson, R.P., Dudík, M., Schapire, R.E., &
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#' Blair, M.E. (2017). Opening the black box: an open-source release of
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#' Maxent. Ecography, 40(7), 887-893.
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#' @references Phillips, S.J., Anderson, R.P. & Schapire, R.E. (2006) Maximum

R/deriveVars.R

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#' maximum likelihood interpretation of MaxEnt. Ecography, 38(2), 172-183.
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#' @references Økland, R.H., Økland, T. & Rydgren, K. (2001).
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#' Vegetation-environment relationships of boreal spruce swamp forests in
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#' Oestmarka Nature Reserve, SE Norway. Sommerfeltia, 29, 1-190.
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#' Østmarka Nature Reserve, SE Norway. Sommerfeltia, 29, 1-190.
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#'
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#' @examples
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#' toydata_dvs <- deriveVars(toydata_sp1po, c("L", "M", "D", "HF", "HR", "T", "B"))

R/plotFOP.R

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#'
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#' If the response variable in \code{data} represents presence/absence data, the
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#' result is an empirical frequency of presence curve, rather than a observed
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#' frequency of presence curve (see Stoea et al. [in press], Sommerfeltia).
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#' frequency of presence curve (see Støa et al. [2018], Sommerfeltia).
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#'
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#' @param data Data frame containing the response variable in the first column
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#' and explanatory variables in subsequent columns. The response variable

README.Rmd

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# MIAmaxent
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## v.1.0.0.9000
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## v.1.1.0
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### Description
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Tools for training, selecting, and evaluating maximum entropy (and standard logistic regression) distribution models. This package provides tools for user-controlled transformation of explanatory variables, selection of variables by nested model comparison, and flexible model evaluation and projection. It follows principles based on the maximum-likelihood interpretation of maximum entropy modeling (Halvorsen et al., 2015), and uses infinitely-weighted logistic regression for model fitting. (Fithian & Hastie, 2013).

README.md

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# MIAmaxent
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## v.1.0.0.9000
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## v.1.1.0
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### Description
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cran-comments.md

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## Test environments
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* local OS X install, R 3.6.0
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* ubuntu 14.04 (on travis-ci), R 3.5.1
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* ubuntu 14.04 (on travis-ci), R 3.6.0
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* win-builder, R devel
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## R CMD check results

man/MIAmaxent.Rd

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man/deriveVars.Rd

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man/plotFOP.Rd

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