Model module to fit a simple MyMaxLike model
MyMaxLike(.df)
.df is data frame that combines the occurrence data and covariate
data. .df is passed automatically in workflow from the process
module(s) to the model module(s) and should not be passed by the user.The mymaxlike method aims to infer the parameters of a
presence-absence logistic regression model using only presence-background
data, in a manner somewhat similar to MaxEnt. The practical utility of this
model has been questioned (see references), since it makes very strong
assumptions about the underlying model which are unlikely to be met in
practice. A more feature-rich version of the model is implemented in the
mymaxlike::mymaxlike package, but that implementation only
accepts raster/point data as input. This module implements a simple version
of the model using the logistic link, in a format that interacts with the
rest of the zoon system.
1.0
2015-11-13
presence/background
J.A. Royle, R.B. Chandler, C. Yackulic, and J.D. Nichols (2012). Likelihood analysis of species occurrence probability from presence-only data for modelling species distributions. Methods in Ecology and Evolution, 3, 545-554.
Hastie, T. & Fithian, W. (2013) Inference from presence-only data; the ongoing controversy. Ecography, 36, 864-867.
Phillips, S.J. & Elith, J. (2013) On estimating probability of presence from use-availability or presence-background data. Ecology, 94, 1409-1419.
Merow, C. & Silander, J.A. (2014) A comparison of MyMaxlike and Maxent for modelling species distributions. Methods in Ecology and Evolution, 5, 215-225.
mymaxlike::mymaxlike
Other model: BiomodModel, GBM,
LogisticRegression,
MachineLearn, MaxEnt,
MaxLike, OptGRaF,
QuickGRaF, RandomForest,
StochasticLogisticRegression,
mgcv