fit2newdata: Make a new data set for prediction

In predict3d: Draw Three Dimensional Predict Plot Using Package 'rgl'

Make a new data set for prediction

Description

Make a new data set for prediction

Usage

fit2newdata(
  fit,
  predictors,
  mode = 1,
  pred.values = NULL,
  modx.values = NULL,
  mod2.values = NULL,
  colorn = 3,
  maxylev = 6,
  summarymode = 1
)

Arguments

fit	An object of class "lm", "glm" or "loess"
predictors	Names of predictor variables in string
mode	A numeric. Useful when the variables are numeric. If 1, c(-1,0,1)*sd + mean is used. If 2, the 16th, 50th, 84th percentile values used. If 3 sequence over a the range of a vector used
pred.values	For which values of the predictors should be used? Default is NULL. If NULL, 20 seq_range is used.
modx.values	For which values of the moderator should lines be plotted? Default is NULL. If NULL, then the customary +/- 1 standard deviation from the mean as well as the mean itself are used for continuous moderators. If the moderator is a factor variable and modx.values is NULL, each level of the factor is included.
mod2.values	For which values of the second moderator should lines be plotted? Default is NULL. If NULL, then the customary +/- 1 standard deviation from the mean as well as the mean itself are used for continuous moderators. If the moderator is a factor variable and modx.values is NULL, each level of the factor is included.
colorn	The number of regression lines when the modifier variable(s) are numeric.
maxylev	An integer indicating the maximum number of levels of numeric variable be treated as a categorical variable
summarymode	An integer indicating method of extracting typical value of variables. If 1, typical() is used.If 2, mean() is used.

Examples

fit=lm(mpg~hp*wt*cyl+carb+am,data=mtcars)
fit2newdata(fit,predictors=c("hp","wt","am"))
fit2newdata(fit,predictors=c("hp","wt","cyl"))
fit2newdata(fit,predictors=c("hp"))
fit2newdata(fit,predictors=c("hp","wt"))
fit=loess(mpg~hp*wt*am,data=mtcars)
fit2newdata(fit,predictors=c("hp"))
## Not run: 
mtcars$engine=ifelse(mtcars$vs==0,"V-shaped","straight")
fit=lm(mpg~wt*engine,data=mtcars)
fit2newdata(fit,predictors=c("wt","engine"))
fit=lm(mpg~wt*factor(vs),data=mtcars)
fit2newdata(fit,predictors=c("wt","vs"))
fit2newdata(lm(mpg~hp*wt,data=mtcars),predictors=c("hp","wt"),mode=3,colorn=30)
fit=lm(mpg~hp*log(wt),data=mtcars)
fit2newdata(fit,predictors=c("hp","log(wt)"))
fit=lm(mpg~hp*wt*factor(vs),data=mtcars)
fit2newdata(fit,predictors=c("hp"))

## End(Not run)
require(moonBook)
fit=lm(log(NTAV)~I(age^2)*sex,data=radial)
fit2newdata(fit,predictors=c("I(age^2)","sex"))

predict3d documentation built on May 29, 2024, 4:25 a.m.