Displaying 20 results from an estimated 59 matches for "multinom".

2005 Apr 13

5

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 script:
library(MASS)
library(nnet)...

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 me...

2011 Apr 08

3

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 deviance is
comparing with the model that correctly predicts each person, not
the multinomial response for each cell of the mininal model&qu...

2005 May 13

3

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...

2004 Oct 28

1

polr versus multinom

Hi,
I am searching for methods to compare regression models with an ordered
categorical response variable (polr versus multinom).
The pattern of predictions of both methods (using the same predictor
variables) is quite different and the AIC is smaller for the multinom
approach. I guess polr has more strict premises for the structure of the
response variable, which methods can be used to test for these premises. If
the AIC i...

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...

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 a...

2008 Aug 11

1

checking if multinom converged

Is anyone aware of a way to check whether multinom has converged by
checking a component of the output ? I''m
not familar with nnet but, since multinom calls nnet , maybe there is an
extra argument once can send to multinom to capture this
information. Thanks.

2008 May 30

1

existing package (mmlcr) modification -- appropriate process?

...nd would like your help in identifying the appropriate
process to follow in order to modify the output from an existing
package. I''ve had difficulty finding an answer online, perhaps because
I am using incorrect terminology.
A package that I am using (mmlcr) invokes another package (multinom).
An output of multinom is the standard errors, but this output is not
provided within mmlcr. I would like to obtain the standard errors as
an output of mmlcr.
For your reference, this is relevant code that I identified in mmlcr,
using getAnywhere{mmlcrfit.multinomlong}:
function (object,...

2008 Dec 19

0

"parm" argument in confint.multinom () nnet package

Dear R users,
The nnet package includes the multinom method for the confint function.
The R Help file (?confint) for the generic function in the stats package
and the help files for the glm and nls methods in the MASS package
indicate that one can use the "parm" argument as "a specification of
which parameters are to be given confi...

2004 May 07

3

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...

2004 May 17

1

residuals in multinom

Hi,
is there a possibility to calculate the different "types" of residuals
directly using the multinom function from MASS as it is possible for the
functions gam, glm
using type="deviance" or "working" or "pearson" or "response"? I tried it
but got always the "response" type, I guess.
thanx
Matthias
**********************************************...

2005 May 09

1

formula restriction in multinom?

Good Day: When I used:
multinom(formula = Y ~ X1 + X2 + X3 + X1:X2 + X1:X3 + X3:X2 + X1^2 + X2^2 +
X3^2, data = DATASET),
I get estimates and AIC for the model containing main effects and
interactions only (no squared terms)...and FYI, all predictors are
continuous. Is this "normal" behavior? If I run this in S-Plus I g...

2010 Mar 17

1

question about multinom function (nnet)

Dear All.
I have the following table that I want to analyze using multinom
function
freq segments sample
4271 Seg1 tumour
4311 Seg2 tumour
3515 Seg1 normal
3561 Seg2 normal
I want to compare model with both factors to the one where only sample
is present.
model1=multinom(freq~segments+sample,data=table)
model2=multinom(freq~ sample,data=table...

2007 Mar 25

2

resolving expand.grid & NA errors

I am hoping for some advice regarding resolving error messages I have
received when trying to use the expand.grid command.
library(nnet)
library(MASS)
library(car)
mod.multacute <-multinom(kc$group ~ kc$in.acute.danger *
kc$violent.convictions, na.rm=T)
summary(mod.multacute, cor=F, Wald=T)
Anova (mod.multacute)
confint (mod.multacute)
> predictors <- expand.grid(group=1:3, in.acute.danger = c("y","n"),
violent.convictions = c("y","n"...

2003 Aug 01

1

behavior of weights in nnet''s multinom()

I see that "case weights" can be optioned in multinom(). I wanted to
make sure I understand what weights= is expecting. My weights (not
really mine but I''m stuck with them) are noninteger, are not scaled to
sum to the sample size, and larger weights are intended to increase
influence.
The description of various types of weights is a per...

2003 Nov 19

0

multinom question

I''d like to fit a multinomial log-linear model for 4 categories of the
form
log[(P(D=i | X)/P(D=0 | X)] = alpha_i + X beta_i ; i=1,2,3
but with beta_1 constrained to zero. Is there a way to impose such a
constraint in the multinom function?
Brad
------------------------------------------------------------------------...

2007 Jan 05

1

Efficient multinom probs

Dear R-helpers,
I need to compute probabilties of multinomial observations, eg by doing the
following:
y=sample(1:3,15,1)
prob=matrix(runif(45),15)
prob=prob/rowSums(prob)
diag(prob[,y])
However, my question is whether this is the most efficient way to do this.
In the call prob[,y] a whole matrix is computed which seems a bit of a
waste.
Is there m...

2004 Nov 02

0

Confident intervals in multinom

Dear R help list,
i''m using multinom (nnet), the results given to me is
the coefficients and std errors.
Is there a way to obtain directly (or in an export to
latex) the odd-ratio (exp(B)) and it''s confident
intervals.
thanks very much for your help
Pierre-Henry Miquel
Universit?? de Lille 2 (M??decine)
France
Vou...

2009 Feb 24

0

multinom() and multinomial() interpretation

Hello and thanks in advance for any advice.
I am not clear how, in practice, the multinom() function in nnet and the
multinomial() function in VGAM differ in terms of interpretation. I
understand that they are fit differently. Are there certain scenarios where
one is more appropriate than the other? In my case I have a dependent
variable with 4 categories and 1 binary and 4 continuou...