R2.L: Lower boundary correlation coefficient.

In RSDA: R to Symbolic Data Analysis

Lower boundary correlation coefficient.

Description

Compute the lower boundary correlation coefficient for two interval variables.

Usage

R2.L(ref, pred)

Arguments

ref	Variable that was predicted.
pred	The prediction given by the model.

Value

The lower boundary correlation coefficient.

Author(s)

Oldemar Rodriguez Rojas

References

LIMA-NETO, E.A., DE CARVALHO, F.A.T., (2008). Centre and range method to fitting a linear regression model on symbolic interval data. Computational Statistics and Data Analysis 52, 1500-1515.

LIMA-NETO, E.A., DE CARVALHO, F.A.T., (2010). Constrained linear regression models for symbolic interval-valued variables. Computational Statistics and Data Analysis 54, 333-347.

See Also

sym.glm

Examples

data(int_prost_train)
data(int_prost_test)
res.cm <- sym.lm(lpsa ~ ., sym.data = int_prost_train, method = "cm")
pred.cm <- sym.predict(res.cm, int_prost_test)
R2.L(int_prost_test$lpsa, pred.cm$Fitted)

RSDA documentation built on Nov. 10, 2023, 5:06 p.m.