similar to: multinom question

I'm having sporadic problems with glm on my alpha workstation running Compaq Tru64 UNIX V5.0 (I can't replicate the problem on my Linux PC). I have the same problem whether I use a version of R built with the native C-compiler or a version compiled with gcc. In both cases I've built with g77. I want to do some simulations with a call to glm in each rep. A simplified version would be

Dear Sir/Madam, I apologize for any cross-posting. I got a simple question, which I thought the R list may help me to find an answer. Suppose we have Y_1, Y_2, ., Y_n ~ Poisson (Lambda_i) and Lambda_i ~Gamma(alpha_i, beta_i). Empirical Bayes Estimator for hyper-parameters of the gamma distr, i.e. (alpha_t, beta_t) are needed. y=c(12,5,17,14) n=4 What about a Hierarchal B ayes

On 16/02/18 15:28, Bert Gunter wrote: > This is really a statistical issue. What do you think the Intercept term > represents? See ?contrasts. > > Cheers, > Bert > > > > Bert Gunter > > "The trouble with having an open mind is that people keep coming along and > sticking things into it." > -- Opus (aka Berkeley Breathed in his "Bloom

I want to estimate the following fixed effect model: y_i,t = alpha_i + beta_1 x1_t + beta_2 x2_i,tx2_i,t = gamma_i + gamma_1 x1_t + gamma_2 Z1_i + gamma_3 Z2_i I can use ivreg from AER to do the iv regression. fm <- ivreg(y_i,t ~ x1_t + x2_i,t | x1_t + Z1_i + Z2_i, data = DataSet) But, I'm not sure how can I add the fixed effects. Thanks! [[alternative HTML

Dear R users, I am using the function "constrOptim" to minimize the -1*log-likelihood where \beta_i>=0 i=1,...,p and \beta_0 is unconstrained. I construct u_i as 0 0 0 ... 0 0 1 0 ... 0 0 0 1 ... 0 . . . ... 0 . . . ... 0 .

Dear people, A somewhat clueless question follows: I just discovered that the lme function in contrib package nlme for R, while similar to the lme function in Splus, does not use the cluster function option. This difference does not appear to be documented in the V&R `R Complements' file. I have data which is divided into 6 groups The lme model is of the form (simplified from the actual

Dear List, I'm just teaching myself semi-parametric techniques. Apologies in advance for the long post. I've got observational data and a longitudinal, semi-parametric model that I want to fit in GAM (or potentially something equivalent), and I'm not sure how to do it. I'm posting this to ask whether it is possible to do what I want to do using "canned" commands

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),

Hi, there is a tiny bug in readconf.c: options->use_privileged_port is always set to 0 regardless of whether -P is specified or not. This has the effect that RhostsAuthentication is disabled even if "RhostsAuthentication yes" is specified. The (trivial) patch is appended below. Martin ======================================================================== Martin Siegert Academic

We are a remote part of the campus and due to security reasons we are loosing access to NFS server which servers the whole university to have access to home directories for all users. We want to make use of the samba client to securely mount FS on our Linux and Unix Solaris computers from the central file server (NetApp). I am new to samba and trying to have some feel whether it is possible

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 confidence intervals, either a vector of numbers or

I am trying to create a LaTex table based on a multinom (nnet) object using the stargazer command. I have created a small data frame to demonstration the problem: data <- data.frame(age=1:21, hight=20:40, ed=c(1,2,3,1,2,3,1,2,3,1,2,3,1,2,3,1,2,3,1,2,3)) data$ed <- as.factor(data$ed) I then make a multinomial model using the command multinom from the nnet package: model <- multinom(ed ~

Hello, I apologize if this seems like an obvious question, but I have been looking everywhere and have yet to find an answer. I am doing a multinomial regression with multinom() in the nnet package. I have a 3 level ordered response (ordered()) variable and 4 predictors, 3 of which are numerical and one which is an ordered factor (also ordered()) with 5 levels (a, b, c, d, e). My question is in

Hello, I am working with s.multinom() from the ade4package. I tried to plot the results of my %PCA (via the function dudi.pca()) followed by a MCOA (mcoa()). But when I give my variables to s.multinom() I get the following Error message: Error in FUN(1:14[[1L]], ...) : number 1 profile without data I know that it has to do with one (or two?) of the first arguments (kpca,sglmarkerfrq) but I just

I have RedHat linux 9 with R 1.8. I'm estimating models with multinom with a dependent variable that has 3 different values. Sometimes the models run fine and I can understand the results. Sometimes when I put in another variable, I see an indication that the estimation did work, but then I can't get the summary method to work. It's like this: > votemn1 <-

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

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.

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

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

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