Best performing model(s) with NRI
Get or mark best performing model(s) between narrow band indices and environmental variables
nri_best_performance(nri, n = 1, coefficient = "p.value",
predictor = 2, abs = FALSE, findMax = FALSE,
...)
mark_nri_best_performance(best, glmnri, n = nrow(best$Indices),
uppertriang = FALSE, ...)nri |
Object of class nri |
glmnri |
Object of class glmnri |
n |
Number of models to return or mark |
coefficient |
Name or index of coefficient to plot |
predictor |
Name or index of term to plot |
abs |
Use absolute value (e.g. for t-values) |
findMax |
Find maximum or minimum values |
best |
Output from |
uppertriang |
Flag to mark the upper triangle |
... |
Further arguments passed to |
Lukas Lehnert
data(spectral_data)
## Calculate all possible combinations for WorldView-2-8
spec_WV <- spectralResampling(spectral_data, "WorldView2-8",
response_function = FALSE)
nri_WV <- nri(spec_WV, recursive = TRUE)
## Build glm-models
glmnri <- glm.nri(nri_WV ~ chlorophyll, preddata = spec_WV)
## Return best 5 models
BM <- nri_best_performance(glmnri, n = 5, coefficient = "p.value")
## Get nri values for the 5 models
nri_BM <- getNRI(nri_WV, BM)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.