ehaGoF (version 0.1.1)

Goodness of Fit : Mean Relative Approximation Error: Mean Relative Approximation Error

Description

Calculates and returns mean relative approximation error (MRAE).

Usage

gofMRAE(Obs, Prd, dgt = 3)

Arguments

Obs

Observed values or target vector.

Prd

Predicted values. Values produced by approximation or regression.

dgt

Number of digits in decimal places. Default is 3.

Value

MeanRelativeApproximationError

Goodness of fit - mean relative approximation error (MRAE)

References

The Connection Dependent Threshold Model for Finite Sources -A Generalization of the Engset Multirate Loss Model - Ioannis D. Moscholios and Michael D. Logothetis.

Competitive adsorption equilibrium modeling of volatile organic compound (VOC) and water vapor onto activated carbon - Imranul I. Laskara, Zaher Hashishoa,<U+204E>, John H. Phillipsb, James E. Andersonc, Mark Nichols.

A new decision tree based algorithm for prediction of hydrogen sulfide solubility in various ionic liquids - Reza Soleimani, Amir Hossein Saeedi Dehaghani, Alireza Bahadori.

Examples

# NOT RUN {
# dummy inputs, independent variable
# integers from 0 to 19
inputs <- 0:19

# dummy targets/observed values, dependent variable
# a product of 2 times inputs minus 5 with some normal noise
targets <- -5 + inputs*1.2 + rnorm(20)

# linear regression model
model<-lm(targets~inputs)

# About the model
summary(model)

# model's predicted values against targets
predicted<-model$fitted.values

# using library ehaGoF for goodness of fit.
library(ehaGoF)

# Goodness of fit : mean relative approximation error (MRAE)
gofMRAE(targets, predicted)
# }