I'm trying to run a logit model in R which has only one predictor. I then
want to construct a data frame with the predictor values on one column and
the probabilities in another column.
Using LDA methodology, I'm able to do the following.
# RUN LDA
r <- lda(y ~ x)
## FIND AND PLOT MODEL PROBABILITIES
xx <- seq(min(x), max(x), length=1000)
pred <- predict(r, data.frame(x=xx), type='response')
yy <- pred$posterior[,2]
t = data.frame(Our_Bid=c(xx), "Pr(win)"=c(yy))
head(t, 10)
> head(t, 10)
Our_Bid Pr.win.
1 0.000000 0.1525893
2 3.096096 0.1538502
3 6.192192 0.1551196
4 9.288288 0.1563976
5 12.384384 0.1576841
6 15.480480 0.1589792
7 18.576577 0.1602829
8 21.672673 0.1615952
9 24.768769 0.1629162
10 27.864865 0.1642459
I want to do something similar with glm but I'm not finding that I'm able
to manipulate predict() such that I can get a similar output as ^^.
mod1 = glm(posted ~ amount, data=ndat, family=binomial(link="probit"))
summary(mod1)
Can anyone help?
Thanks!
--
*Abraham Mathew
Statistical Analyst
**720-648-0108*
*abmathe...@gmail.com
*
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About.Me <http://about.me/abraham_mathew>*
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