Displaying 20 results from an estimated 2000 matches similar to: "Multinomial Nested Logit package in R?"
2002 Jul 29
0
multinomial probit
Is there any library for fitting multinomial probit using either likelihood
or the "method of simulated moments" or both.
I presume it would be possible to write a family function in VGAM for the
multinomial probit, but was hoping that someone has done it already.
Thanking you as always.
Vumani Dlamini
CSO-Swaziland
2004 Dec 03
3
multinomial probit
Hello All,
I'm trying to run a multinomial probit on a dataset with 28 data
points and five levels (0,1,2,3,4) in the latent choice involving
response variable.
I downloaded the latest mnp package to run the regression. It starts
the calculation and then crashes the rpogram. I wish I could give the
error message but it literally shuts down R without a warning.
I'm using the R
2007 Apr 21
1
Fitting multinomial response in structural equation
Hi - I am confronting a situation where I have a set of structural equation and one or two of my responses are multinomial. I understand that sem would not deal with the unordered response. So I am thinking of the following two ways:
1. Expanding my response to a new set of binary variables corresponding to each label of my multinomial response. Then use each of these as a separate response in my
2012 Nov 06
1
Multinomial MCMCglmm
Thanks for your answers Stephen and Ben,
I hope I am posting on the correct list now.
I managed so far to run the multinomial model with random effect with the
following command:
MCMCglmm(fixed=cbind(Apsy,Mygl,Crle,Crru,Miag,empty) ~
habitat:trait,random=~idh(trait):mesh,family="multinomial12",
data=dataA,rcov=~trait:units)
(where multiple responses are different species,
Habitat
2005 Jul 27
2
logistic regression: categorical value, and multinomial
I have two questions:
1. If I want to do a binomial logit, how to handle the
categorical response variable? Data for the response
variables are not numerical, but text.
2. What if I want to do a multinomial logit, still
with categorical response variable? The variable has 5
non-numerical response levels, I have to do it with a
multinomial logit.
Any input is highly appreciated! Thanks!
Ed
2007 Jul 19
2
multinomial logit estimation
Good morning,
I'd like to estimate a simple multinomial logit model in R (not a McFadden conditional logit). For instance, I'd like to estimate the probability of someone having one of eight titles in a company with the independent variables being the company characteristics. A binary logit is well documented. What about the multinomial?
Thanks,
Walt Paczkowski
2009 Aug 01
4
Likelihood Function for Multinomial Logistic Regression and its partial derivatives
Hi,
I would like to apply the L-BFGS optimization algorithm to compute the MLE
of a multilevel multinomial Logistic Regression.
The likelihood formula for this model has as one of the summands the formula
for computing the likelihood of an ordinary (single-level) multinomial logit
regression. So I would basically need the R implementation for this formula.
The L-BFGS algorithm also requires
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
2004 Sep 23
3
multinomial logistic regression
Hi, how can I do multinomial logistic regression in R?
I think glm() can only handle binary response
variable, and polr() can only handle ordinal response
variable. how to do logistic regression with
multinomial response variable?
Thanks
__________________________________
2008 May 13
1
How to get predicted marginal (aka predicted mean) after multinomial logistic?
I tried to use the effect() to get predicted marginals for multinomial
logistic as I did for general logistic regression, but failed. Is there
anyway to do that?
Thx!
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2010 Sep 11
2
Generating multinomial distribution and plotting
I have had plenty of succes generating one dimensional variables and plotting
them, but what do i do for more (specifically 2) dimensional multinomial
variables?
I figure i have to create a vector consisting of two 1 dim normallly
distributed variables, that way i can also control the correlation.
But how do i do this :) ?
Many thanks
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2011 Dec 23
2
Latent class multinomial (or conditional) logit using R?
Hi everyone?
Does anybody know how can I estimate a
Latent class multinomial (or conditional) logit using R?
I have tried flexmix, poLCA, and
they do not seem to support this model.
thanks in advance
adan
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2006 Jun 18
1
Method for selection bias with multinomial treatment
I have to the treatment effect base on the observational data.And the
treatment variable is multinomial rather than binary.Because the
treatment assignment is not random,so the selection-bias exists.Under
this condition,what's the best way to estimate the treatment effect?
I know that if the treatment is binary,I can use propensity score
matching using MatchIt package.But what about
2011 May 25
1
Multinomial Logistical Model
On May 24, 2011; 11:06pm Belle wrote:
> Does anyone know how to run Multinomial logistical Model in R in order to
> get predicted probability?
Yes. I could stop there but you shouldn't. The author of the package
provides plenty of examples (and two good vignettes) showing you how to do
this. Suggest you do some work in that area. Look especially at how model
formulas are
2003 Jan 22
1
negative multinomial regression models
Hello,
I''ve spent a lot of time during the past month trying to get negative
multinomial regression models for clustered event counts as described in
(Guang Guo. 1996. "Negative Multinomial Regression Models For Clustered
Event Counts." Sociological Methodology 26: 113-132., abstract at
http://depts.washington.edu/socmeth2/4abst96.htm) implemented in R. A
FORTRAN version of the
2005 Nov 10
2
Help to multinomial analyses
Dear Sirs,
Could you please be so kind as to send us some information on residuals in
multinomial logistic models? Is it possible to use R software?
We thank you in advance.
Sincerely yours
Luciana Alves,MSc
Beatriz Leimann, MD
--
Luciana Correia Alves
Doutoranda em Sa??de P??blica
ENSP - Fiocruz
2010 Jun 06
2
fitting multinomial logistic regression
Sir,
I want to fit a multinomial logistic regression in R.I think mlogit() is the
function for doing this. mlogit () is in packege globaltest.But, I can not
install this package. I use the following:
install.packages("globaltest")
Can you help me?
Regards,
Suman Dhara
[[alternative HTML version deleted]]
2009 Oct 08
1
unordered multinomial logistic regression (or logit model) with repeated measures (I think)
I am attempted to examine the temporal independence of my data set and think
I need an unordered multinomial logistic regression (or logit model) with
repeated measures to do so. The data in question is location of chickens.
Chickens could be in any one of 5 locations when a snapshot sample was
taken. The locations of chickens (bird) in 8 pens (pen) were scored twice a
day (AMPM) for 20 days
2012 Dec 03
2
Solving a multinomial gompertz partial differential equation in r
I haven't used r in quite a while but would like to get back into it. I
have a problem that I would like to solve with r. I have some multinomial
data that looks to follow an asymmetric sigmoidal growth pattern. Solving
a multinomial gompertz partial differential equation in r is what I’m after.
Would anyone be able to provide me the code and packages to do something
like this?
Regards,
2012 Mar 21
1
Multinomial Logit data arrangement
Dear all,
I am having a hard time attempting to do a multinomial logit modeling in R.
I am trying to analyze a dataset whereby there are 3 scenarios with 4
difference choice parameters. In particular ? I am having a hard time
arranging this into a .csv format. What sorts of headings should I put in
the column headers to reflect the variables and parameters for the total
number of choice made