DAAG: CVlm – R documentation

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CVlm

Cross-Validation for Linear Regression

Description

This function gives internal and cross-validation measures of predictive accuracy for multiple linear regression. (For binary logistic regression, use the CVbinary function.) The data are randomly assigned to a number of ‘folds’. Each fold is removed, in turn, while the remaining data is used to re-fit the regression model and to predict at the deleted observations.

Usage

CVlm(data = DAAG::houseprices, form.lm = formula(sale.price ~ area),
              m = 3, dots = FALSE, seed = 29, plotit = c("Observed","Residual"),
              main="Small symbols show cross-validation predicted values",
              legend.pos="topleft", printit = TRUE)
cv.lm(data = DAAG::houseprices, form.lm = formula(sale.price ~ area),
              m = 3, dots = FALSE, seed = 29, plotit = c("Observed","Residual"),
              main="Small symbols show cross-validation predicted values",
              legend.pos="topleft", printit = TRUE)

Arguments

`data`	a data frame
`form.lm`	a formula or `lm` call or `lm` object
`m`	the number of folds
`dots`	uses pch=16 for the plotting character
`seed`	random number generator seed
`plotit`	This can be one of the text strings `"Observed"`, `"Residual"`, or a logical value. The logical `TRUE` is equivalent to `"Observed"`, while `FALSE` is equivalent to `""` (no plot)
`main`	main title for graph
`legend.pos`	position of legend: one of `"bottomright"`, `"bottom"`, `"bottomleft"`, `"left"`, `"topleft"`, `"top"`, `"topright"`, `"right"`, `"center"`.
`printit`	if TRUE, output is printed to the screen

Details

When plotit="Residual" and there is more than one explanatory variable, the fitted lines that are shown for the individual folds are approximations.

Value

The input data frame is returned, with additional columns Predicted (Predicted values using all observations) and cvpred (cross-validation predictions). The cross-validation residual sum of squares (ss) and degrees of freedom (df) are returned as attributes of the data frame.

Author(s)

J.H. Maindonald

Examples

CVlm()
## Not run: 
CVlm(data=nihills, form.lm=formula(log(time)~log(climb)+log(dist)),
          plotit="Observed")
CVlm(data=nihills, form.lm=formula(log(time)~log(climb)+log(dist)),
     plotit="Residual")
out <- CVlm(data=nihills, form.lm=formula(log(time)~log(climb)+log(dist)),
               plotit="Observed")
out[c("ms","df")]

## End(Not run)

DAAG

Data Analysis and Graphics Data and Functions

v1.24

GPL-3

Authors

John H. Maindonald and W. John Braun

Initial release