sym.predict: Predict method to CM and CRM regression model

In RSDA: R to Symbolic Data Analysis

Predict method to CM and CRM regression model

Description

To execute predict method the Center Method (CR) and Center and Range Method (CRM) to Linear regression.

Usage

sym.predict(model, ...)

## S3 method for class 'symbolic_lm_cm'
sym.predict(model, new.sym.data, ...)

## S3 method for class 'symbolic_lm_crm'
sym.predict(model, new.sym.data, ...)

## S3 method for class 'symbolic_glm_cm'
sym.predict(model, new.sym.data, response, ...)

## S3 method for class 'symbolic_glm_crm'
sym.predict(model, new.sym.data, response, ...)

Arguments

model	The output of lm method.
...	additional arguments affecting the predictions produced.
new.sym.data	Should be a symbolic data table read with the function read.sym.table(...).
response	The number of the column where is the response variable in the interval data table.

Value

sym.predict produces a vector of predictions or a matrix of predictions and bounds with column names fit, lwr, and upr if interval is set. For type = 'terms' this is a matrix with a column per term and may have an attribute 'constant'

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)
model <- sym.lm(lpsa ~ ., sym.data = int_prost_train, method = "cm")
pred.cm <- sym.predict(model, int_prost_test)
pred.cm

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