Description Usage Arguments Value Examples
Title
1 2 3 |
n |
number of y values to generate |
link |
link function "id", "sqrt", "log", "logit", "cloglog" |
dist |
one of "normal", "poisson", "binomial" |
beta |
6-vector of regression coefficients |
xes |
list describing all regressors as either number of levels or range of continuous uniform |
s |
sd if "normal", size if "binomial" |
seed |
for random number generator |
data.frame of y vector and X matrix
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | ## Not run:
plotglm(icon=E.coli,colo=c("gray","yellow"),col="darkgrey",
data = rglm(dist="poisson",xes=list(x1=c(10,170),x2=3,x3=9,x4=2)))
# Regressoren bedeuten: x-Achse, Farbe, Größe, Drehung
daten <- rglm(dist="poisson",
xes=list(x1=c(10,20),x2=2,x3=c(0.7,2.5),x4=c(-2,6)),
beta=c(1,0.5,2,.03,1,0.7))
plotglm(icon=E.coli,colo=c("gray","green"),col="darkgrey",rot=10,
iex=.2, str=0.3, data = daten)
daten <- rglm(n=12,dist="binomial",
xes=list(x1=c(7,14),x2=1,x3=1,x4=1),
beta=c(0,0.032,0,0,0,0))
daten[,5] <- daten[,1]
daten[,4] <- daten[,2]/10
plotglm(icon=zebrafish,colo=c("n"),col="black",rot=pi,
iex=.04, str = 1.3, data = daten)
est <- glm(y~x.x1,family='binomial',data=daten)
new <- data.frame(x.x1=(1:200)/10)
odd <- exp(predict(est,newdata=new))
P <- odd/(1+odd)
lines(new$x.x1,P)
abline(v=-est$coefficients[1]/est$coefficients[2],h=c(0,0.5,1),lty=2)
## End(Not run)
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