Learn R Programming

IPEC (version 1.1.2)

Root Mean Square Curvature Calculation

Description

Calculates the RMS intrinsic and parameter-effects curvatures of a nonlinear regression model. The curvatures are global measures of assessing whether a model/data set combination is close-to-linear or not. See Bates and Watts (1980) and Ratkowsky and Reddy (2017) for details.

Copy Link

Version

Install

install.packages('IPEC')

Monthly Downloads

302

Version

1.1.2

License

GPL (>= 2)

Maintainer

Peijian Shi

Last Published

September 26th, 2025

Functions in IPEC (1.1.2)

aic

Akaike Information Criterion (AIC) Calculation Function
biasIPEC

Bias Calculation Function
IPEC-package

Root Mean Square Curvature Calculation
confcurves

Wald Confidence Curves and the Likelihood Confidence Curves
derivIPEC

Derivative Calculation Function
crops

Whole-plant biomass Data of 12 Species of Crops
bic

Bayesian Information Criterion (BIC) Calculation Function
curvIPEC

RMS Curvature Calculation Function
bootIPEC

Bootstrap Function for Nonlinear Regression
isom

Data on Biochemical Oxygen Demand
skewIPEC

Skewness Calculation Function
leaves

Leaf Data of Parrotia subaequalis (Hamamelidaceae)
shoots

Height Growth Data of Bamboo Shoots
parinfo

Detailed Information of Estimated Model Parameters
fitIPEC

Nonlinear Fitting Function