Goodness of Fit - Coefficient of Variation {ehaGoF}

Coefficient of Variation.

Description

Calculates and returns goodness of fit - coefficient of variation (CV).

Usage

gofCV(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

CoeficientOfVariation

Goodness of fit - coefficient of variation (CV).

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

Examples

# 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)

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

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

# Goodness of fit - coefficient of variation (CV)
gofCV(targets, predicted)