logit: Generalized logit and inverse logit function

In hSDM: Hierarchical Bayesian Species Distribution Models

Generalized logit and inverse logit function

Description

Compute generalized logit and generalized inverse logit functions.

Usage

logit(x, min = 0, max = 1)
inv.logit(x, min = 0, max = 1)

Arguments

x	value(s) to be transformed
min	Lower end of logit interval
max	Upper end of logit interval

Details

The generalized logit function takes values on [min, max] and transforms them to span [-Inf,Inf] it is defined as:

y = log(\frac{p}{(1-p)})

where

p=\frac{(x-min)}{(max-min)}

The generized inverse logit function provides the inverse transformation:

x = p' (max-min) + min

where

p'=\frac{exp(y)}{(1+exp(y))}

Value

Transformed value(s).

Author(s)

Gregory R. Warnes <[e-mail]>

Examples

## Not run: 
  x <- seq(0,10, by=0.25)
  xt <- logit(x, min=0, max=10)
  cbind(x,xt)

  y <- inv.logit(xt, min=0, max=10)
  cbind(x,xt,y)  

## End(Not run)

hSDM documentation built on Sept. 8, 2023, 6:08 p.m.