Displaying 9 results from an estimated 9 matches for "predprob".
2011 Oct 19
1
hypothetical prediction after polr
Dear R-Help listers,
I am trying to estimate an proportional odds logistic regression model
(or ordered logistic regression) and then make predictions by
supplying a hypothetical x vector. However, somehow this does not
work. I guess I must have missed something here. I first used the polr
function in the MASS package, and I create a data frame and supply it
to the predict function (see below):
2012 Jul 13
1
Vuong test
...) and Zero-inflated model.
NB1 <- glm(, , family = quasipoisson), it is an
object of class: "glm" "lm"
zinb <-
zeroinfl( dist = "negbin") is an object of class: "zeroinfl"
when applying vuong
function I get the following:
vuong(NB1, zinb)
Error en predprob.glm(m1) :
your object of class glm is unsupported by
predprob.glmyour object of class lm is unsupported by predprob.glm
Any help will be really appreciated.
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2007 May 18
1
A programming question
...constant.
A simple toy example is like this
Range for my variables is defined as follows
y=0 or 1, x1 = -10 to 10, x2=-40 to 100, x3 = -5 to 5
Model
output <- glim(y ~ x1+x2+x3 -1, family=binomial(link="probit"))
outcoef <- output$coef
xbeta <- as.matrix(cbind(x1, x2, x3)
predprob <- pnorm(xbeta%*%outcoef)
now I have the predicted probabilities for y=1 as defined above. My problem is as follows
Keep X2 at 20 and X3 at 2. Then compute the predicted probability (predprob) for the entire range of X1 ie from -10 to 10 with an increment of 1.
Therefore i need the predicted...
2006 Oct 14
0
help on voung test
Dear All,
I am using the function vuong of the package pscl to compare 2 non nested glm models with a numeric response.
I did the following
m1<-glm(y ~x ,data=xxx)
m2<-glm(y ~z , data=xxx)
When calling the vuong function I get the following message:
> vuong(m1,m2)
Error in predprob.glm(m1) : your object of class glm is unsupported by predprob.glmyour object of class lm is unsupported by predprob.glm
My guess is that this function does not support numeric response!!!!! How can I solve the problem?
Any help will be really appreciated.
mirko
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2006 Oct 15
0
problems perfroming the vuong test
Dear All,
I am using the function vuong of the package pscl to compare 2 non nested
glm models with a numeric response.
I did the following
m1<-glm(y ~x ,data=xxx)
m2<-glm(y ~z , data=xxx)
When calling the vuong function I get the following message:
> vuong(m1,m2)
Error in predprob.glm(m1) : your object of class glm is unsupported by
predprob.glmyour object of class lm is unsupported by predprob.glm
My guess is that this function does not support numeric response!!!!! How
can I solve the problem?
Any help will be really appreciated.
mirko
2009 Aug 21
1
Question about validating predicted probabilities
Hello,
Frank was nice enough to point me to the val.prob function of the Design
library.
It creates a beautiful graph that really helps me visualize how well my
model is predicting probabilities.
By default, there are two lines on the graph
1) fitted logistic calibration curve
2) nonparametric fit using lowess
Right now, the nonparametric line doesn't look very good.
The
2008 Oct 01
1
Negative Binomial Predictions
Good Day All,
I have a negative binomial model which I have developed using the MASS
library. I now would like to develop some predictions from it.
Running the predict.glm (stats library) using type="response" gives me a
non-integer value which was rather puzzling. I would like to confirm
that this is actually the mean predicted value of the probability mass
function as opposed
2004 Apr 08
0
R: lines and glm
...)
plot(x, y, pch = 16, col = "darkblue",
main = expression(paste("Scatter diagram of ",
italic(y[t]), "against ", italic(x[t]))),
xlab = expression(italic(x[t])),
ylab = expression(italic(y[t])))
model<-glm(y ~ x, family = binomial)
predProbs<-predict(model,data.frame(x=seq(min(x), max(x), length.out=100)), type="response")
lines(seq(min(x), max(x), length.out=100), predProbs, col=2, lwd=2)
Note also that it is not a good idea to name "t" a R object, since the name is reserved for a special function.
Stefan...
2011 Oct 11
1
Count model prediction
Hello ;
I am doing a regression of count data (number of award and there are some
covariates)
I have estiamted the parameters of negative binomial distribuion (lambda is
a function of covaraites, GLM model) by glm.nb function and training
dataset.
Now I want to predict the number of award (for example y=0, y=1, y=2,) or
testing dataset. I dont know how to calculate this numbers?
I would be very