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IPEC (version 1.1.1)

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.

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Version

Install

install.packages('IPEC')

Monthly Downloads

289

Version

1.1.1

License

GPL (>= 2)

Maintainer

Peijian Shi

Last Published

July 23rd, 2025

Functions in IPEC (1.1.1)

curvIPEC

RMS Curvature Calculation Function
confcurves

Wald Confidence Curves and the Likelihood Confidence Curves
bootIPEC

Bootstrap Function for Nonlinear Regression
bic

Bayesian Information Criterion (BIC) Calculation Function
fitIPEC

Nonlinear Fitting Function
aic

Akaike Information Criterion (AIC) Calculation Function
biasIPEC

Bias Calculation Function
crops

Whole-plant biomass Data of 12 Species of Crops
derivIPEC

Derivative Calculation Function
IPEC-package

Root Mean Square Curvature Calculation
isom

Data on Biochemical Oxygen Demand
parinfo

Detailed Information of Estimated Model Parameters
shoots

Height Growth Data of Bamboo Shoots
leaves

Leaf Data of Parrotia subaequalis (Hamamelidaceae)
skewIPEC

Skewness Calculation Function