predicted.prevalence {PresenceAbsence} | R Documentation |
Predicted Prevalence
Description
predicted.prevalence
calculates the observed prevalence and predicted prevalence for one or more models at one or more thresholds.
Usage
predicted.prevalence(DATA, threshold = 0.5, which.model = (1:N.models), na.rm = FALSE)
Arguments
DATA |
a matrix or dataframe of observed and predicted values where each row represents one plot and where columns are:
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threshold |
a cutoff values between zero and one used for translating predicted probabilities into 0 /1 values, defaults to 0.5. | ||||||||||||||||||||||||
which.model |
a number indicating which models from DATA should be used | ||||||||||||||||||||||||
na.rm |
a logical indicating whether missing values should be removed |
Details
Function will work for one model and multiple thresholds, or one threshold and multiple models, or multiple models each with their own threshold.
Value
returns a dataframe where:
[,1] | threshold | thresholds used for each row in the table |
[,2] | Obs.Prevalence | this will be the same in each row |
[,3] | Model 1 | Predicted prevalence for first model |
[,4] | Model 2 | Predicted prevalence for second model, etc... |
Author(s)
Elizabeth Freeman eafreeman@fs.fed.us
Examples
data(SIM3DATA)
predicted.prevalence(SIM3DATA)
predicted.prevalence(SIM3DATA,threshold=11,which.model=1,na.rm=FALSE)
predicted.prevalence(SIM3DATA,threshold=c(.2,.5,.7),na.rm=FALSE)