Displaying 20 results from an estimated 5000 matches similar to: "multi-class modeling"
2008 Jun 20
1
omnibus LR in multinomial model
If one estimates a model using multinom, is it possible to perform the
omnibus LR test ( the analogue to omnibus F in linear models ) using
the output
from multinom ? The residual deviance is there but I was hoping I could
somehow pull out the deviance based on just using an intercept ?
Sample code is below from the CAR book but I wasn't sure how to do it
based on that example. Thanks
2005 Apr 12
1
factors in multinom function (nnet)
Dear All:
I am interested in multinomial logit models (function multinon, library nnet) but I'm having troubles in choose whether to define the predictors as factors or not.
I had posted earlier this example (thanks for the reply ronggui):
worms<- data.frame(year= rep(2000:2004, c(3,3,3,3,3)),age=rep(1:3,5),
2018 May 01
2
Specifying priors in a multi-response MCMCglmm
Hi all,
I previously emailed about a multinomial model, and after seeking some
additional help, realized that since my response/outcome variables are not
mutually exclusive, I need to use a multi-response model that is *not*
multinomial. I'm now trying to figure out how to specify the priors on the
multi-response model. Any help would be much appreciated.
My data look like this:
X
2005 Apr 13
2
multinom and contrasts
Hi,
I found that using different contrasts (e.g.
contr.helmert vs. contr.treatment) will generate
different fitted probabilities from multinomial
logistic regression using multinom(); while the fitted
probabilities from binary logistic regression seem to
be the same. Why is that? and for multinomial logisitc
regression, what contrast should be used? I guess it's
helmert?
here is an example
2006 Feb 22
2
does multinomial logistic model from multinom (nnet) has logLik?
I want to get the logLik to calculate McFadden.R2 ,ML.R2 and
Cragg.Uhler.R2, but the value from multinom does not have logLik.So my
quetion is : is logLik meaningful to multinomial logistic model from
multinom?If it does, how can I get it?
Thank you!
ps: I konw VGAM has function to get the multinomial logistic model
with logLik, but I prefer use the function from "official" R
2012 Jan 05
2
difference of the multinomial logistic regression results between multinom() function in R and SPSS
Dear all,
I have found some difference of the results between multinom() function in
R and multinomial logistic regression in SPSS software.
The input data, model and parameters are below:
choles <- c(94, 158, 133, 164, 162, 182, 140, 157, 146, 182);
sbp <- c(105, 121, 128, 149, 132, 103, 97, 128, 114, 129);
case <- c(1, 3, 3, 2, 1, 2, 3, 1, 2, 2);
result <- multinom(case ~ choles
2018 May 01
0
Specifying priors in a multi-response MCMCglmm
1. (Mainly) Statistical issues are generally off topic on this list.
You might want to try the r-sig-mixed-models list instead.
2. However, I think a better answer is to seek local statistical
expertise in order to have an extended discussion about your research
intent in order to avoid producing yet more irreproducible
psychological research.
Cheers,
Bert
Bert Gunter
"The trouble with
2006 Jun 27
1
weights in multinom
Best R Help,
I like to estimate a Multinomial Logit Model with 10 Classes. The
problem is that the number of observations differs a lot over the 10
classes:
Class | num. Observations
A | 373
B | 631
C | 171
D | 700
E | 87
F | 249
G | 138
H | 133
I | 162
J | 407
Total: 3051
Where my data looks like:
x1 x2 x3 x4 Class
1 1,02 2 1 A
2 7,2 1 5 B
3 4,2 1 4 H
1 4,1 1 8 F
2 2,4 3 7 D
1 1,2 0 4 J
2 0,9
2005 May 13
1
multinom(): likelihood of model?
Hi all,
I'm working on a multinomial (or "polytomous") logistic regression
using R and have made great progress using multinom() from the nnet
library. My response variable has three categories, and there are two
different possible predictors. I'd like to use the likelihoods of
certain models (ie, saturated, fitteds, and null) to calculate
Nagelkerke R-squared values for
2011 Apr 08
1
multinom() residual deviance
Running a binary logit model on the data
df <- data.frame(y=sample(letters[1:3], 100, repl=T),
x=rnorm(100))
reveals some residual deviance:
summary(glm(y ~ ., data=df, family=binomial("logit")))
However, running a multinomial model on that data (multinom, nnet)
reveals a residual deviance:
summary(multinom(y ~ ., data=df))
On page 203, the MASS book says that "here the
2004 May 07
1
scores from multinomial logistic regression
Dear all,
I'm interested in extracting the score from multinomial logistic regression
models fit using multinom, to assess the stregth of assocation of the
parameter with the response (akin to the score from clogit/cox regression).
currently I'm using R 1.8.1.
Is there a function that will extract the score from a multinom object or
how i can get back to it? or from using glm?
I
2009 Jun 13
1
Insignificant variable improves AIC (multinom)?
Hi,
I am trying to specify a multinomial logit model using the multinom function from the nnet package. Now I add another independent variable and it halves the AIC as given by summary(multinom()). But when I call Anova(multinom()) from the car package, it tells me that this added variable is insignificant (Pr(>Chisq)=0.39). Thus, the improved AIC suggests to keep the variable but the Anova
2005 Nov 17
1
access standard errors from multinom model
Dear R users,
I'm using a multinomial LOGIT model to analyse choice behaviour of consumers
(as part of my masters thesis research).
Using the R documentation and search on the R website I have a working
script now.
Parameters are estimated and I can access them via
coefficients(multinom.out).
In order to see if the parameters are significant I like to access the
standard errors in the
2003 Jun 03
1
Logistic regression problem: propensity score matching
Hello all.
I am doing one part of an evaluation of a mandatory welfare-to-work
programme in the UK.
As with all evaluations, the problem is to determine what would have
happened if the initiative had not taken place.
In our case, we have a number of pilot areas and no possibility of
random assignment.
Therefore we have been given control areas.
My problem is to select for survey individuals in
2003 Jan 24
3
Multinomial Logit Models
Hi
I am wanting to fit some multinomial logit models (multinom command in
package nnet)
Is it possible to do any model checking techniques on these models
e.g. residual, leverage etc. I cannot seem to find any commands that
will allow me to do this.
Many thanks
----------------------
L.E.Gross
L.E.Gross at maths.hull.ac.uk
2007 Jun 21
2
Multinomial models
Hello,
I am VERY new to R (one week) and I am trying to run a multinomial logit model.
The model I am using is
> model1 <- multinom(Y ~ X1 + X2 + , ..., Xn)
if I put in
> summary(model1)
I get
#Error in function (classes, fdef, mtable) :
unable to find an inherited method for function "fitted", for
signature "multinom"
and if I put in
> coef(model1)
2004 Sep 27
1
multinom object :way of plotting??
Dear all,
I'm fitting a multinom function to my dataset (multinom(outcome~age+K+D))
and I need to present my results on a poster. Does someone know a nice way
of doing that? I think I saw in an archive that you cannot plot a
multinom.object, is it true?
Thank you by advance for your help,
Cheers
Camille
2000 Mar 20
3
: multinom()
Dear R users,
Does anyone know if it is possible to use multinom to do a polychotomous
fit using one categorical and one numeric variable as response. The
doc. for multinom states that for formula , response can be K>2 classes.
Is this 2 and more, or as I have understood it only greater than 2. I
have tried fitting my data, but have only encountered error messages.
On another note, Is it
2004 Feb 23
3
library nnet
DeaR useRs:
I am looking for a function which fits a multinomial model and in Baron?s
page I find the function "multinom" in package "nnet" but this package is
deprecated.
I suppose that this function is now in other package but I can't find it.
Can you help me?
Thanks.
2006 Feb 22
2
How can one use R-code and R-functions within C-Code?
Dear everyone,
the following problem: Our group has written a lengthy program in c++, to which we would like to add some additional features. Because we are not sure if those features are actually useful, we would prefer to take a "quick and dirty" approach just to try them out. The additional feature is that in every iteration of the algorithm membership-probabilities should by