Nonlinear Goodness-of-fit and Determination Coefficients — nlmR • usefr

This function returns goodness-of-fit criteria for nonlinear model selection. Adjusted R squared (rho), the AIC, and BIC are estimated.

nlmR(object)

Arguments

object: An object which inherits from 'nls' class, typically returned after performing a nonlinear regression fit with function nls or nlsLM.

Details

The Stein's formula for adjusted R squared (rho) is applied as an estimator of the average cross-validation predictive power (1).

References

1. Stevens JP. Applied Multivariate Statistics for the Social Sciences. Fifth Edit. Routledge Academic; 2009.

See also

mcgoftest for Bootstrap test for Goodness of fit.

Author

Robersy Sanchez - 10/22/2020

Examples

### Examples from 'nls' doc
DNase1 <- subset(DNase, Run == 1)

## using a selfStart model
fm1DNase1 <- nls(density ~ SSlogis(log(conc), Asym, xmid, scal), DNase1)
nlmR(fm1DNase1)
#>   Adj.R.Square       rho       AIC       BIC
#> 1    0.9989789 0.9982739 -76.41642 -73.32607