Goodness of Fit : R-Squared {ehaGoF}

R-Squared (Coefficient of Determination)

Description

Calculates and returns R-squared (coefficient of determination).

Usage

gofRSq(Obs, Prd, dgt = 3)

Arguments

Obs

Observed or measured values or target vector.

Prd

Predicted or fitted values by the model. Values produced by approximation or regression.

dgt

Number of digits in decimal places. Default is 3.

Value

RSquared

Goodness of fit - coefficient of determination (R-squared)

Author(s)

Prof. Dr. Ecevit Eyduran, TA. Alper Gulbe

References

Comparison of Different Data Mining Algorithms for Prediction of Body Weight From Several Morphological Measurements in Dogs - S Celik, O Yilmaz.

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

# dummy inputs, independent variable
# integers from 0 to 99
inputs <- 0:99

# dummy targets/observed values, dependent variable
# a product of 2*times inputs minus 5 with some normal noise
targets <- -5 + inputs*1.2 + rnorm(100)

# 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 : coefficient of determination (R-squared)
gofRSq(targets, predicted)