similar to: Re: termplot

Displaying 20 results from an estimated 9000 matches similar to: "Re: termplot"

2004 Jan 24
1
Enhancement to termplot()
I'd like to make the following change to termplot(): Add panel=points as an extra parameter. Replace if (partial.resid) points(xx, pres[, i], cex = cex, pch = pch, col = col.res, ...) by if (partial.resid) panel(xx, pres[, i], cex = cex, pch = pch, col = col.res, ...) Also, I think, add col.smooth, span and iter as named parameters; see below.
2004 Jan 04
0
termplot; failure to subset non-dataframe carriers (PR#6327)
termplot() does not carry subsetting over to carriers that are in the environment but not in the data frame. This generates a "subscript out of bounds" error. > data(ToothGrowth) > logdose <- log(ToothGrowth$dose) > tooth.lm <- lm(len ~ logdose, data=ToothGrowth) > termplot(tooth.lm) ## Works fine > toothVC2.lm <- lm(len ~ poly(dose,2),
2007 Jul 03
1
termplot - changes in defaults
While termplot is under discussion, here's another proposal. I'd like to change the default for partial.resid to TRUE, and for smooth to panel.smooth. I'd be surprised if those changes were to break existing code. John Maindonald email: john.maindonald at anu.edu.au phone : +61 2 (6125)3473 fax : +61 2(6125)5549 Centre for Mathematics & Its Applications, Room
2001 Jan 27
1
termplot fails for composite non-factor terms (PR#828)
I am running R 1.2.1 under Windows 98SE. termplot() currently fails when there are composite terms, thus: > library(mass) > data(hills) > hills.lm <- lm(time ~ climb + poly(dist, 2), data = hills) > termplot(hills.lm) Hit <Return> to see next plot: Error in eval(expr, envir, enclos) : Object "dist" not found The call >
2004 Mar 18
1
termplot has problems with a single term (fix included) (PR#6679)
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
2001 Sep 24
1
R-devel Digest V1 #314
R-devel Digest Monday, September 24 2001 Volume 01 : Number 314 In this issue: [Rd] R 1.3.1 fails 'make check' on arm in the Bessel example (PR#1097) [Rd] Bug list summary (automatic post) [Rd] (PR#1089) Can be closed See the end of the digest for information about r-devel-digest ---------------------------------------------------------------------- Date: Fri, 21
2009 Oct 14
0
Error from termplot() with make.panel.svysmooth() for complex survey data
Greetings, I am using library(survey) to analyze some complex sample data. After fitting a model I tried to use termplot() with make.panel.svysmooth(), but I received an error (see below). Could someone help me interpret the error message so I can make the necessary corrections? The make.panel.svysmooth() function seems to work fine, and termplot() worked fine after I dropped the smoother.
2011 Jun 06
1
Possible bug in termplot function (stats package) ?
Hi all, I noticed some very odd behaviour in the termplot function of the stats package due to the following lines : 18. if (is.null(data)) 19. data <- eval(model$call$data, envir) This one will look in the global environment, and renders the two lines after this 20. if (is.null(data)) 21. data <- mf completely obsolete. If nothing is found, an error is returned. If
2003 Dec 16
0
Help w/ termplot & predict.coxph/ns
I am fitting a cox PH model w/ 2 predictors, x1 = 0/1 treatment variable and x2=continuous variable. I am using natural splines (ns) to model the effect of x2. I would like to examine the estimated effect of x2 on the hazard. I have tried various approaches (below; let model.fit= fitted model using coxph in survival library): 1. The simplest method appears to be using termplot(model.fit).
2004 Jan 22
1
Bug in termplot?
Hi, Is this a bug in termplot, or (once again) do I just not understand what R is really doing? I am using termplot to contruct partial residual plots, 1. For all terms at once 2. One term at a time but I get different results from these two methods. To give a concrete example, I would have thought the top and bottom rows of the plot constructed with the following code would be identical.
2000 Oct 27
1
par(ask=T) in termplot() (PR#711)
At 11:57 25/10/00 +0100, Brian Ripley wrote: >> Date: mer., 25 oct. 2000 12:38:55 +0200 >> From: Emmanuel Paradis <paradis@isem.univ-montp2.fr> > >> I think it would be nice to have par(ask=T) set by default in termplot(), >> like it is in plot.lm(). > >Well, it isn't really the default in plot.lm, the default for `ask' being > >interactive()
2012 Oct 19
1
Addition of plot=F argument to termplot
I have a suggested addition to termplot. We have a local mod that is used whenever none of the termplot options is quite right. It is used here almost daily for Cox models in order to put the y axis on a risk scale: ---- fit <- coxph(Surv(time, status) ~ ph.ecog + pspline(age), data=lung) zz <- termplot(fit, se=TRUE, plot=FALSE) yy <- zz$age$y + outer(zz$age$se, c(0, -2, 2),
2013 Feb 18
0
Small suggestion for termplot
Brian, I used termplot(..., plot=FALSE) recently in R-devel: works like a charm. Thanks much for the update. Our in-house "gamterms" function, which this obviates, would also return the "constant" attribute from the underlying predict(..., type="terms") call. I have occasionally found this useful, and so it would be a worthwhile addition to termplot.
2018 Jan 11
0
termplot intervals - SE or CI?
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. > >
2011 Dec 14
1
termplot & predict.lm. some details about calculating predicted values with "other variables set at the mean"
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) :
2009 Jan 19
1
termplot
I have used glm and stepAIC to choose a best model. I can use termplot to assess the contribution of each explanatory variable in the glm. However the final model after running stepAIC includes interaction terms, and when I do termplot I get "Error in `[.data.frame`(mf, , i) : undefined columns selected". I also see the termplot detail saying "Nothing sensible happens for
2003 Mar 26
0
termplot (PR#2687)
# r-bugs@r-project.org `termplot' bombs if the original dataset contains NAs in the predictors, even if these were ignored during fitting: test> bug.data_ data.frame( x=c(1:3, NA), y=runif( 4)) test> lm.tpbug_ lm( y~x, data=bug.data) test> termplot( lm.tpbug) Error in xy.coords(x, y, xlabel, ylabel, log) : subscript out of bounds A simple fix seems to be add the
2018 Jan 10
1
termplot intervals - SE or CI?
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,
2006 Jul 15
1
termplot and ylim
Hi together, I always get an error message with using ylim in termplot(), like this: > x<-(1:10) > y<-(10:1) > l<-lm(y~x) > termplot(l,ylim=c(1,2)) Is this a bug, or is there another possibility to do that? Especially, I would like to use term.plot() for gamlss objects. Thanks for your help! Andreas -- Echte DSL-Flatrate dauerhaft f?r 0,- Euro*!
2010 Aug 26
3
Using termplot() with transformations of x
Hi all I was playing with termplot(), and came across what appears to be an inconsistency. It would appreciate if someone could enlighten me: > # First, generate some data: > y <- rnorm(100) > x <- runif(length(y),1,2) > # Now find the log of x: > logx <- log(x) > > # Now fit two models that are exactly the same, but specified differently: > m1 <-