dr_maxnet: Density-ratio SDM estimation with Maxnet

In bmaitner/pbsdm: Small Sample Size Species Distribution Modeling

Density-ratio SDM estimation with Maxnet

Description

dr_maxnet is an internal function for density-ratio estimation with Maxnet

Usage

dr_maxnet(
  presence_data = NULL,
  background_data = NULL,
  projection_data = NULL,
  formula = NULL,
  regmult = 1,
  regfun = maxnet.default.regularization,
  addsamplestobackground = TRUE,
  clamp = TRUE,
  verbose = FALSE,
  method,
  type = c("link", "exponential", "cloglog", "logistic"),
  object = NULL
)

Arguments

presence_data	dataframe of covariates
background_data	dataframe of covariates
projection_data	dataframe of covariates
formula	Maxnet formula to use. Default (NULL) will use the Maxnet default. This parameter is called "f" in the maxnet function, but is renamed here as using "t" and "f" as object names is frowned upon.
regmult	Maxnet regularization multiplier. Default is 1.
regfun	Maxnet regularization function. Default is the Maxnet default.
addsamplestobackground	If TRUE (the default), any presences that aren't in the background will be added.
clamp	If TRUE (the default), predictions will be limited to ranges seen in the training dataset.
method	one of either "fit" or "predict"
type	Type of response required. Defaults to link, exponential, cloglog, and logistic.
object	fitted object returned by a dr_... function. Only needed when method = "predict"

Note

The options f, regmult, regfun, and addSamplestobackground are only used when method == "predict", the options clamp and type are only used when method == "predict". See the much better documentation for maxnet for more details.

bmaitner/pbsdm documentation built on Feb. 8, 2025, 2:27 p.m.