similar to: Last Call: Who says this is not a bug in delete.response()?

I posted this one as an R bug (https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=14767), but Prof. Ripley says I'm premature, and I should raise the question here. Here's the behavior I assert is a bug: The output from delete.response on a terms object alters the formula by removing the dependent variable. It removes the response from the "variables" attribute and it changes

Below is a SIMEX object that was generated with the "simex" function from the "simex" package applied to a logistic regression fit. From this mountain of information I would like to extract all of the values summarized in this line: .. ..$ variance.jackknife: num [1:5, 1:4] 1.684 1.144 0.85 0.624 0.519 ... Can someone suggest how to go about doing this? I can extract the

Someone sent me a bug report for survival2.44.1-1 that involves a model with both cluster and offset.? It turns out to be a 3 part issue with [.terms and my own untangle.specials routine.?? I've spent an evening sorting out the details. ? 1. The delete.response() function doesn't remove the response from the dataClasses attribute, which leads to a later failure in [.terms for

Martin, ? There are a couple of issues with [.terms that have bitten my survival code.? At the useR conference I promised you a detailed (readable) explanation, and have been lax in getting it to you. The error was first pointed out in a bugzilla note from 2016, by the way.? The current survival code works around these. Consider the following formula: <<testform>>=

Hi, I've performed an lda and obtained a classification table for some of my data: > efa.dfa<-lda(groups~.,efa.scores.8,CV=T) > str(efa.dfa) List of 5 $ class : Factor w/ 2 levels "1","2": 1 2 1 2 1 1 2 2 1 2 ... $ posterior: num [1:160, 1:2] 0.99083 0.00852 0.93983 0.23186 0.85931 ... ..- attr(*, "dimnames")=List of 2 .. ..$ : chr [1:160]

Hi! The kernlab function kpca() mentions that new observations can be transformed by using predict. Theres also an example in the documentation, but as you can see i am getting an error there (As i do with my own data). I'm not sure whats wrong at the moment. I haven't any predict functions written by myself in the workspace either. I've tested it with using the matrix version and the

Greetings R experts, I'm having some difficulty recovering lda objects that I've saved within sublists using the save.image() function. I am running a script that exports a variety of different information as a list, included within that list is an lda object. I then take that list and create a list of that with all the different replications I've run. Unfortunately I've been

I'm making some functions to illustrate regressions and I have been staring at termplot and predict.lm and residuals.lm to see how this is done. I've wondered who wrote predict.lm originally, because I think it is very clever. I got interested because termplot doesn't work with interactive models: > m1 <- lm(y ~ x1*x2) > termplot(m1) Error in `[.data.frame`(mf, , i) :

Hi: When I call str() on an mlogit object, I seem to get warnings. This code is from an example provided in the mlogit documentation: library(mlogit) data("Train", package="mlogit") tr<-mlogit.data(Train, shape="wide", choice="choice", varying=4:11, sep="", alt.levels=c(1,2), id="id")

Greetings: I'm still working on functions to make it easier for students to interpret regression predictions. I am working out a scheme to more easily create "newdata" objects (for use in predict functions). This has been done before in packages like Zelig, Effects, rms, and others. Nothing is "exactly right," though. Stata users keep flashing their "predicted

Is anybody working on a way to standardize the creation of "newdata" objects for predict methods? When using predict, I find it difficult/tedious to create newdata data frames when there are many variables. It is necessary to set all variables at the mean/mode/median, and then for some variables of interest, one has to insert values for which predictions are desired. I was at a

Gracias a todos por las recomendaciones. Ya me he puesto en contacto con el autor y le explicado donde esta el error. Es tan fácil como que han cambiado la estructura de los objetos tipos lmer desde la versión 2.15.3 con lo que su paquete dejo de funcionar. Por suerte la nueva estructura conserva por lo menos la parte necesaria para hacer sus funciones. Se localizar el fallo y como arreglarlo, lo

On Thu, 18 Mar 2004 k.hansen@biostat.ku.dk wrote: > The bug exists on R-1.9.0-alpha compiled the 10/3. > > Termplot has a problem if either the model only contains a single term > or if asked to plot a single term. In addition there are problems with > the option se = TRUE. I can't reproduce this in either R-devel or 1.8.1, and termplot hasn't changed since January. I do

Hace unos meses os escribir para comunicaros que había un fallo en esta función. Como os prometí os comento la respuesta por si alguno está interesado en utilizar el paquete LMERconvenientsfucntions Dear Javier, The package has been updated and should work for you fine now. Note that function mcp.fnc does not return the fourth plot (dffits) anymore. We still have to figure out a way to compute

There is a bug in `predict' whereby the order of variables sometimes gets re-arranged compared to the original fit, and then disaster results. Specifically, the 'variables' and 'predvars' attributes of a 'terms' object get out of synch. This only happens when the terms in the original formula get re-ordered during fitting: test> scrunge.data_ data.frame(

I am fitting a cox PH model w/ 2 predictors, x1 = 0/1 treatment variable and x2=continuous variable. I am using natural splines (ns) to model the effect of x2. I would like to examine the estimated effect of x2 on the hazard. I have tried various approaches (below; let model.fit= fitted model using coxph in survival library): 1. The simplest method appears to be using termplot(model.fit).

At 11:57 25/10/00 +0100, Brian Ripley wrote: >> Date: mer., 25 oct. 2000 12:38:55 +0200 >> From: Emmanuel Paradis <paradis@isem.univ-montp2.fr> > >> I think it would be nice to have par(ask=T) set by default in termplot(), >> like it is in plot.lm(). > >Well, it isn't really the default in plot.lm, the default for `ask' being > >interactive()

From ?termplot: col.se, lty.se, lwd.se: color, line type and line width for the ?twice-standard-error curve? when ?se = TRUE?. ...which is findable, but might usefully also be made explicit in the definition of the se= argument. -pd > On 10 Jan 2018, at 23:27 , Eric Goodwin <Eric.Goodwin at cawthron.org.nz> wrote: > > Thanks for your prompt reply Duncan. > >

Hi, Is this a bug in termplot, or (once again) do I just not understand what R is really doing? I am using termplot to contruct partial residual plots, 1. For all terms at once 2. One term at a time but I get different results from these two methods. To give a concrete example, I would have thought the top and bottom rows of the plot constructed with the following code would be identical.

Thanks for your prompt reply Duncan. I had indeed assumed they were what the help file says until observation raised doubts, which is why I queried it. >From reading the code for termplot(), it seems that either the predict() function doesn't return the 1x standard error, or the curves plotted by the termplot() function are not 1x standard errors. If they're not 1x standard errors,