nlmR: Nonlinear Goodness-of-fit and Determination Coefficients

View source: R/nlmR.R

nlmRR Documentation

Nonlinear Goodness-of-fit and Determination Coefficients

Description

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

Usage

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).

Author(s)

Robersy Sanchez - 10/22/2020

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.

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)


genomaths/usefr documentation built on July 28, 2022, 12:31 p.m.