Fits a simple logistic regression model, but then samples a single draw of the model coefficients (with probability proportional to their likelihood) and uses these for future prediction
StochasticLogisticRegression(.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.Coefficients are simulated from the likelihood density using the approximate hessian matrix, under an assumption of multivariate normality. This module is intended for use in a Monte Carlo simulation procedure to propagate uncertainty through an analysis. It is not intended to be used on its own!
presence/absence
0.1
2016-06-16
Other model: BiomodModel
, GBM
,
LogisticRegression
,
MachineLearn
, MaxEnt
,
MaxLike
, MyMaxLike
,
OptGRaF
, QuickGRaF
,
RandomForest
, mgcv