Goodness-of-fitting (GOF) of fine curve fitting results.
get_GOF(fit) get_GOF.fFITs(fFITs)
fit | Object returned by |
---|---|
fFITs |
|
meth
: The name of fine curve fitting method
RMSE
: Root Mean Square Error
NSE
: Nash-Sutcliffe model efficiency coefficient
R
: Pearson-Correlation
R2
: determined coefficient
pvalue
: pvalue of R
n
: The number of observations
https://en.wikipedia.org/wiki/Nash-Sutcliffe_model_efficiency_coefficient
https://en.wikipedia.org/wiki/Pearson_correlation_coefficient
#> Error in library(phenofit): there is no package called ‘phenofit’# simulate vegetation time-series fFUN = doubleLog.Beck par = c( mn = 0.1, mx = 0.7, sos = 50, rsp = 0.1, eos = 250, rau = 0.1) t <- seq(1, 365, 8) tout <- seq(1, 365, 1) y <- fFUN(par, t) methods <- c("AG", "Beck", "Elmore", "Gu", "Zhang") # "Klos" too slow fFITs <- curvefit(y, t, tout, methods)#>#>#>#>#>#>#>#>#>#># multiple years fits <- list(`2001` = fFITs, `2002` = fFITs) l_param <- get_param(fits) d_GOF <- get_GOF(fits) d_fitting <- get_fitting(fits) l_pheno <- get_pheno(fits, "AG", IsPlot=TRUE)