rfmods: Random forest models for metrics

In fawda123/ASCI: Calculate scores for the Algal Stream Condition Index

Random forest models for metrics

Description

List of random forest models for predictive metrics

Usage

rfmods

Format

A list with six elements, one for each predictive metric and a final element for conductivity estimates:

diatoms.cnt.spp.most.tol

randomForest

diatoms.EpiRho.richness

randomForest

diatoms.prop.spp.IndicatorClass_TN_low

randomForest

diatoms.prop.spp.Planktonic

randomForest

diatoms.prop.spp.Trophic.E

randomForest

diatoms.Salinity.BF.richness

randomForest

hybrid.cnt.spp.IndicatorClass_TP_high

randomForest

hybrid.cnt.spp.most.tol

randomForest

hybrid.EpiRho.richness

randomForest

hybrid.OxyRed.DO_30.richness

randomForest

hybrid.prop.spp.Planktonic

randomForest

hybrid.prop.spp.Trophic.E

randomForest

hybrid.Salinity.BF.richness

randomForest

cond.qrf

quantregForest

Examples

data(rfmods)

fawda123/ASCI documentation built on April 12, 2024, 4:16 a.m.