similar to: Avoding scoping problems with model fit objects

Dear R users: I am not entirely convinced that clogit gives me the correct result when I use pspline() and maybe you could help correct me here. When I add a constant to my covariate I expect only the intercept to change, but not the coefficients. This is true (in clogit) when I assume a linear in the logit model, but the same does not happen when I use pspline(). If I did something similar

I have about 20 000 cases with discrete variables (some are counts, some are factors). I'm interested in fitting a series of models outcome ~ 1 outcome ~ sex outcome ~ sex + age outcome ~ age * sex outcome ~ age * sex + location ... I do NOT expect to get any statistical significance out of this at all; it's purely exploratory (this is a small sample of the full data set). I'm

>On Sat, 11 Jun 2005, John Fox wrote: > >>Dear Marc, >> >>I get the same results -- same coefficients, standard errors, and fitted >>probabilities -- from multinom() and glm(). It's true that the deviances >>differ, but they, I believe, are defined only up to an additive constant: > >Yes. There are many variations on the definition >of (residual)

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

> From: "Alan T. Arnholt" <arnholt at math.appstate.edu> > To: Bill Venables <William.Venables at cmis.CSIRO.AU> > Cc: r-help at stat.math.ethz.ch, arnholt at math.appstate.edu > Subject: Re: [R] Lack of Fit test > Date: Wed, 23 Feb 2000 09:40:21 -0500 (EST) > X-Authentication: none > > > I guess my question was not adequately stated when I sent

On Mon, 25 Feb 2002, David Meyer wrote: > Prof Brian D Ripley wrote: > > > > Thanks, fixed now. > > > > Why were you calling delete.response on an object with no response, BTW? > > I used it in predict.svm(), and the terms-object contained in the svm > model just happens to have no response for the ``one-class > classification'' if svm was called

Hi, I noted this message yesterday in R-devel. I think it would sensible to package a patched version while 2.12.2 is not delivered. ---------- Forwarded Message ---------- Subject: [Rd] Warning: you may need to use R-patched with recent R distros Date: Monday 31 January 2011, 19:48:33 From: Prof Brian Ripley <ripley at stats.ox.ac.uk> To: R-devel at r-project.org Two things have

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

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

On 29 Oct 2004, Peter Dalgaard wrote: > deepayan@stat.wisc.edu writes: > > > > foo <- expression(alpha, beta, gamma) > > > foo[2] > > expression(beta) > > > foo[2] <- NA > > > foo ## or str(foo) > > Segmentation fault > > > > (Same behaviour in R 1.9.1) > > > > 'foo[[2]] <- NA' works fine, though.

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 <-

Brian, So let me ask an r-core opinion. Should I change the default to model=TRUE? Survival is heavily used and there is something to be said for consistency within the central packages. Sometimes old habits die hard, and there is a "save memory" part of me that hates to save a large object that likely won't be used. Not nearly as relevant today as when I started my

Hi R-Helpers , am working on nnet package.Multinom() has an option for finding the goodness of fit by giving the AIC value. Does nnet also gives some value to determine the accuracy. If not, can you guide me with some procedure to figure out the accuracy/goodness of fit of nnet model? Thanks in advance. -- View this message in context:

Two things have emerged in testing on x86_64 Fedora 14 which mean that a recent R-patched is probably needed. 1) That OS uses zlib 1.2.5: that claims to be binary-compatible with zlib 1.2.3 but is not, as we found (painfully) on Windows. The remedy was to remap _all_ the symbols in R's own copy of zlib (not just those zlib arranged to remap). The symptoms were crashes using packages XML

Thanks to Andy Liaw, Roger Peng, Thomas Lumley, Brian Ripley and Peter Dalgaard, all of whom addressed my questions or threads arising from them. The full messages were posted to the list so this is a brief summary: Andy Liaw explained the difference between lexical and dynamic scoping and the rationale behind the choice of lexical scoping for R. Roger Peng showed how to modify fnB. Brian

This message is in MIME format. The first part should be readable text, while the remaining parts are likely unreadable without MIME-aware tools. --27501778-1317196171-1259330723=:5696 Content-Type: TEXT/PLAIN; CHARSET=ISO-8859-7; format=flowed Content-Transfer-Encoding: 8BIT Content-ID: <alpine.LFD.2.00.0911271406411.5696 at toucan.stats.ox.ac.uk> Did you read the help page?

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

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

I want to analyse data with an unordered, multi-level outcome variable, y. I am asking for the appropriate method (or R procedure) to use for this analysis. > N <- 500 > set.seed(1234) > data0 <- data.frame(y = as.factor(sample(LETTERS[1:3], N, repl = T, + prob = c(10, 12, 14))), x1 = sample(1:7, N, repl = T, prob = c(8, + 8, 9, 15, 9, 9, 8)), x2 = sample(1:7, N, repl =

anova() on three or more objects behaves inconsistently in R. In R anovalist.lm does a sequential ANOVA using pairwise F tests, ignoring all the other objects, so the larger of the two models provides the denominator. In S anova.lmlist uses the denominator from the largest model (smallest residual df) in the set, as does anova.glmlist in both. I suggest that R's anovalist.lm is wrong (that