MLRMPA (version 1.0)

Rsquared: Squared-R

Description

'Rsquared' is used to calculate coefficient of determination.

Usage

Rsquared(y.pre, y)

Arguments

y.pre

calculated response values of training set

y

observed values of training set, a 1*m dataframe (m is the sample number of the training set)

Value

R2

the correlation coefficient

Details

'squared-R' is the correlation coefficient of the model, which reprensents the interpreting ability of the model. It is a statistic used in the context of statistical models whose main purpose is either the prediction of future outcomes or the testing of hypotheses, on the basis of other related information. It provides a measure of how well observed outcomes are replicated by the model, as the proportion of total variation of outcomes explained by the model.

See Also

lm

Examples

u <- c(5,10,15,20,30,40,60,80,100)
lot1 <- c(118,58,42,35,27,25,23,20,18)
lot2 <- c(69,35,26,21,18,16,13,12,6)
data <- data.frame(cbind(u,lot1,lot2))
lm <- lm(u~.,data=data)
y.pre<-fitted(lm)
y<-u
Rsquared(y.pre,y)
summary(lm)$r.squared