ggPredict {ggiraphExtra} | R Documentation |
Visualize predictions from the multiple regression models.
Description
Visualize predictions from the multiple regression models.
Usage
ggPredict(
fit,
colorn = 4,
point = NULL,
jitter = NULL,
se = FALSE,
show.summary = FALSE,
colorAsFactor = FALSE,
digits = 2,
interactive = FALSE,
...
)
Arguments
fit |
a model object for which prediction is desired. |
colorn |
Integer. Number of subgroups of color variables. |
point |
Logical. Whether or not draw each point |
jitter |
Logical. Whether or not jitter points |
se |
Logical. Whether or not draw se |
show.summary |
Logical. Whether or not show summary |
colorAsFactor |
Logical. Whether or not treat color variable as categorical variable |
digits |
An integer indicating the number of decimal places |
interactive |
A logical value. If TRUE, an interactive plot will be returned |
... |
additional arguments affecting the predictions produced. |
Examples
require(moonBook)
require(ggplot2)
require(ggiraph)
require(plyr)
fit=lm(NTAV~age*weight,data=radial)
fit=lm(NTAV~age*weight*DM,data=radial)
fit=lm(NTAV~age+DM,data=radial)
ggPredict(fit,interactive=TRUE)
require(TH.data)
fit=glm(cens~pnodes*horTh,data=GBSG2,family=binomial)
ggPredict(fit,se=TRUE)
fit1=glm(cens~pnodes*age,data=GBSG2,family=binomial)
ggPredict(fit1)
ggPredict(fit1,colorn=100,jitter=FALSE,interactive=TRUE)
fit2=glm(cens~pnodes*age*horTh,data=GBSG2,family=binomial)
ggPredict(fit2,colorn=100,jitter=FALSE,interactive=TRUE)
[Package ggiraphExtra version 0.3.0 Index]