# get_GOF: get_GOF In phenofit: Extract Remote Sensing Vegetation Phenology

## Description

Goodness-of-fitting (GOF) of fine curve fitting results.

## Usage

 ```1 2 3``` ```get_GOF(fit) get_GOF.fFITs(fFITs) ```

## Arguments

 `fit` Object returned by `curvefits`. `fFITs` `fFITs` object returned by `curvefit()`.

## Value

• `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

## References

1. https://en.wikipedia.org/wiki/Nash-Sutcliffe_model_efficiency_coefficient

2. https://en.wikipedia.org/wiki/Pearson_correlation_coefficient

`curvefit()`

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16``` ```library(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) ```

### Example output ```
```

phenofit documentation built on Oct. 15, 2021, 5:09 p.m.