maxnet: Maxent over glmnet

In mrmaxent/maxnet: Fitting 'Maxent' Species Distribution Models with 'glmnet'

Maxent over glmnet

Description

Maxent species distribution modeling using glmnet for model fitting

Using lp for the linear predictor and entropy for the entropy of the exponential model over the background data, the values plotted on the y-axis are:

• lp if type is "link"

• exp(lp) if type is "exponential"

• 1-exp(-exp(entropy+lp)) if type is "cloglog"

• 1/(1+exp(-entropy-lp)) if type is "logistic"

Usage

maxnet(
  p,
  data,
  f = maxnet.formula(p, data),
  regmult = 1,
  regfun = maxnet.default.regularization,
  addsamplestobackground = T,
  ...
)

maxnet.default.regularization(p, m)

maxnet.formula(p, data, classes = "default")

Arguments

p	numeric, a vector of 1 (for presence) or 0 (for background)
data	a matrix or data frame of predictor variables
f	formula, determines the features to be used
regmult	numeric, a constant to adjust regularization
regfun	function, computes regularization constant for each feature
addsamplestobackground	logical, if TRUE then add to the background any presence sample that is not already there
...	not used
m	a matrix of feature values
classes	charcater, continuous feature classes desired, either "default" or any subset of "lqpht" (for example, "lh")

Value

Maxnet returns an object of class maxnet, which is a list consisting of a glmnet model with the following elements added:

betas

nonzero coefficients of the fitted model

alpha

constant offset making the exponential model sum to one over the background data

entropy

entropy of the exponential model

penalty.factor

the regularization constants used for each feature

featuremins

minimum of each feature, to be used for clamping

featuremaxs

maximum of each feature, to be used for clamping

varmin

minimum of each predictor, to be used for clamping

varmax

maximum of each predictor, to be used for clamping

samplemeans

mean of each predictor over samples (majority for factors)

levels

levels of each predictor that is a factor

Author(s)

Steve Phillips

Examples

## Not run: 
  library(maxnet)
  data(bradypus)
  p <- bradypus$presence
  data <- bradypus[,-1]
  mod <- maxnet(p, data)
  plot(mod, type="cloglog")
  mod <- maxnet(p, data, maxnet.formula(p, data, classes="lq"))
  plot(mod, "tmp6190_ann")

## End(Not run)

mrmaxent/maxnet documentation built on Jan. 12, 2023, 8:20 a.m.