predOmniProd: Predict OMNISCIENT Gaussian model object using permutation of...

In adamlilith/enmSdmPredImport: Testing measures of predictor importance in species distribution models

Predict OMNISCIENT Gaussian model object using permutation of linear terms

Description

Predict OMNISCIENT Gaussian model object using permutation of linear terms (i.e., not interactions–see predictOmniscientPermIa.

Usage

predOmniProd(x1, x2, mu1, mu2, sigma1, sigma2, rho, product, extreme)

Arguments

x1	Numeric, values of the first variable.
x2,	Numeric, values of the second variable.
mu1	Numeric, mean of x1 in a Gaussian function. The maximum value of the function with respect to x1 occurs at this value of x1.
mu2	Numeric, mean of x2 in a Gaussian function. The maximum value of the function with respect to x2 occurs at this value of x2.
sigma1	Numeric, standard deviation of x1 in a Gaussian function. Scales the width of the response to x1.
sigma2	Numeric, standard deviation of x2 in a Gaussian function. Scales the width of the response to x2.
rho	Numeric, strength of covariance between x1 and x2.
product	Numeric vector representing pre-multiplied (and possibly permuted) product: (x1 - mu1) * (x2 - mu2).
extreme	Numeric, most extreme value of product possible in this milieu. Used to standardize result to (0, 1].

Value

Numeric vector.

adamlilith/enmSdmPredImport documentation built on Dec. 31, 2022, 5:40 p.m.