makepredictcall.dw_transformer: Utility Function for Safe Prediction with 'datawizard'...

In datawizard: Easy Data Wrangling and Statistical Transformations

Utility Function for Safe Prediction with datawizard transformers

Description

This function allows for the use of (some of) datawizard's transformers inside a model formula. See examples below.

Currently, center(), standardize(), normalize(), & rescale() are supported.

Usage

## S3 method for class 'dw_transformer'
makepredictcall(var, call)

Arguments

var	A variable.
call	The term in the formula, as a call.

Value

A replacement for call for the predvars attribute of the terms.

See Also

stats::makepredictcall()

Examples

data("mtcars")
train <- mtcars[1:30, ]
test <- mtcars[31:32, ]

m1 <- lm(mpg ~ center(hp), data = train)
predict(m1, newdata = test) # Data is "centered" before the prediction is made,
# according to the center of the old data

m2 <- lm(mpg ~ standardize(hp), data = train)
m3 <- lm(mpg ~ scale(hp), data = train) # same as above
predict(m2, newdata = test) # Data is "standardized" before the prediction is made.
predict(m3, newdata = test) # Data is "standardized" before the prediction is made.


m4 <- lm(mpg ~ normalize(hp), data = mtcars)
m5 <- lm(mpg ~ rescale(hp, to = c(-3, 3)), data = mtcars)

(newdata <- data.frame(hp = c(range(mtcars$hp), 400))) # 400 is outside original range!

model.frame(delete.response(terms(m4)), data = newdata)
model.frame(delete.response(terms(m5)), data = newdata)

datawizard documentation built on Oct. 6, 2024, 1:08 a.m.