similar to: behavior of weights in nnet's multinom()

Not real data. It was gererated randomly. The original codes are the following: par(mfrow=c(2,1)) n <- 500 ######################### #DATA GENERATING PROCESS# ######################### x1 <- rnorm(n,0,1) x2 <- rchisq(n,df=3,ncp=0)-3 sigma <- 1 u1 <- rnorm(n,0,sigma) ylatent1 <-x1+x2+u1 y1 <- (ylatent1 >=0) # create the binary indicator ####################### #THE

I'm trying to do the following: For each ordered pair of a data frame (D1) containing longitudes and latitudes and unique point IDs, calculate the distance to every point in another data frame (D2) also containing longitudes, latitudes and point IDs, and return to a new variable in D1 the point ID of the nearest element of D2. Dramatis personae (mostly self-explanatory): D1$long

R-users, (forgive my return adres) I've been breaking my head why R---which i find fabulous, by the way---does not pipe interactive output through a pager (more or less), like it does with help(), or like GNU Octave does with arrays with more than terminal height rows. Maybe it is my installation (Debian/GNU Linux). Maybe it is my configuration, but i don't think so because with

Hello Why this works: ncota <- 1 nslope <- 29 resul <- matrix(rep(0,ncota*nslope*4),ncota*nslope,4) But this doesn't? ncota <- 1 sini <- 0.1; sfin <- 1.5; spaso <- 0.05; nslope <- 1+((sfin-sini)/spaso) resul <- matrix(rep(0,ncota*nslope*4),ncota*nslope,4) I guess the problem is that the division gives a noninteger number. How can I get the second one work? I

Hello all, I have a fairly simple data manipulation question. Say I have a dataframe like this: dat <- as.data.frame(runif(7, 3, 5)) dat$cat <- factor(c("1","4","13","1","4","13","13A")) dat runif(7, 3, 5) cat 1 3.880020 1 2 4.062800 4 3 4.828950 13 4 4.761850 1 5 4.716962 4 6

A question about the inner workings of glm() and dpois(): Suppose I call glm(y ~ x, family=poisson, weights = w) where y contains NON-INTEGER (but still nonnegative) values. (a) Does glm() still correctly maximise the weighted Poisson loglikelihood ? (i.e. the function given by the same formal expression as the weighted loglikelihood of independent Poisson variables Y_i except that the

Hi, I have count data that have been meddled with enough to make them non integers. Using glm(poisson) returns a "non integer" error but glm(quasipoisson) does not. Just wondering if anyone knows if I am violating the assumptions of a quasipoisson error structure by using these non-integer response data? Thanks! I'd welcome your thoughts and/or references... Mark

>>>>> "PD" == Peter Dalgaard <p.dalgaard@biostat.ku.dk> >>>>> on 24 Nov 2004 18:32:15 +0100 writes: PD> tlumley@u.washington.edu writes: >> > > dhyper() does not allow non-integer values for input >> parameters m and n. >> > >> > this is in contrast to the other functions in the

I have a question about stepAIC and extractAIC and why they can produce different answers. Here's a stepAIC result (slightly edited - I removed the warning about noninteger #successes): stepAIC(glm(formula = (Morbid_70_79/Present_70_79) ~ 1 + Cohort + Cohort2, family = binomial, data = ghs_70_79, subset = ghs_70_full),direction = c("backward")) Start: AIC=3151.41

This message is in MIME format. The first part should be readable text, while the remaining parts are likely unreadable without MIME-aware tools. ---1936847065-1111238301-1101309010=:193006 Content-Type: TEXT/PLAIN; charset=iso-8859-1; format=flowed Content-Transfer-Encoding: QUOTED-PRINTABLE On Wed, 24 Nov 2004 Erik.Jorgensen@agrsci.dk wrote: > > dhyper() does not allow non-integer

Hallo Everybody Consider the following vector a=1:10 b=20:30 c=40:50 x=c(a,b,c) I need a function that can tell me that there are three set of continuos sequences and that the first is from 1:10, the second from 20:30 and the third from 40:50. In other words: a,b, and c. regards Christiaan [[alternative HTML version deleted]]

R core team - It took far, far longer than I anticipated, but I have finally finished the next release of the survival code. Primary changes 1. The source has been migrated to Rforge. This will now be the primary source. I've used SCCS -> rcs -> cvs and now svn. Further changes will be someone else's problem. I expect that maintaince will now begin to migrate to a larger

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 continuous

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

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 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

Dear all users, I"d like to ask you how to make decision about colinearity among categorical independent variables when the model is multinomial logistic regression. Any help is appreciated, Niklas [[alternative HTML version deleted]]

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

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 ------------------------------------------------------------------------- Brad McNeney email: mcneney at stat.sfu.ca

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 Vous manquez d??espace pour stocker vos mails ?