similar to: lattice graph/ panel.superpose / groups

Full_Name: Volker Franz Version: 1.5.1 OS: Debian-Linux Submission from: (NULL) (134.176.77.64) Hi, working with the panel.superpose function, I found out that this function does not pass the subscripts and groups arguments to panel.groups functions. In my view, this seems an unnecessary restriction, because the subscripts-mechanism which allows to access the original data should also work if

Hi, I am trying to superimpose (overlay) regression lines to scatter plots by groups with xyplot (dysfunctional code below). However, my call of panel.superpose breaks down because of the subscripts requirement. I tried to research the documentation and examples, but I cannot figure out how to make xyplot plug subscripts to a panel... call. Could you have a look? It would be greatly appreciated.

Dear R Users, I have an xyplot() where different plotting symbols are used for subgroups (originally used within S-Plus, but hopefully it?s also applicable to R users). How can I fit separate regression lines for every subgroup? So far, I can only plot the overall fitted line. The code looks like this: trellis.device() sps<-trellis.par.get("superpose.symbol") sps$pch<-1:7

I would like to plot 3 best-fit models in a single panel of a lattice plot, superimposed on 3 corresponding datasets in the same panel. My goal is to show the models as lines of 3 different colors, and the data as points whose colors correspond to the model colors. In essence, I have two levels of grouping: 1) model vs. data, and 2) model number. Since there is only one ?groups? variable, I

Hello. I know how to make a bar plot in which a numeric y variable is plotted against some grouping variable X (say, groups A, B, C) when this grouping variable is subdivided into each of two subgroups; so the bars would be: (group A subgroup 1) beside (group A subgroup 2), then (group B subgroup 1) beside (group B subgroup 2), and so on. This is done using the beside=TRUE argument in the

Hi. I'm embarking on my first attempt at creating my own panel function for lattice graphics, and despite all of my online research and pouring through the documentation, I cannot figure out how to solve my particular problem. Hopefully, a generous fellow R user can help. I have some data that is split into two groups: some "actual" data, and some simulated data,

Dear R listers, I am trying to create a lattice plot with independent regression lines per group for each panel, plus one overall regression line per panel. I succeed in having the separate regression lines for each group per panel, but I can't figure out how to add the overall regression line over all groups. I have learnt a lot from the list, but I can't find an example for what I want

Background: OS: Linux Mandrake 10.1 release: R 2.0.0 editor: GNU Emacs 21.3.2 front-end: ESS 5.2.3 --------------------------------- Colleagues I'm plotting fish egg densities in temperature-salinity space (i.e. mean temperature ~ mean salinity | fish egg densities) for two survey years. The bivariate plot is overlaid on a temperature ~ salinity plot (not means) showing the distribution of

Background: OS: Linux Mandrake 10.1 release: R 2.0.0 editor: GNU Emacs 21.3.2 front-end: ESS 5.2.3 --------------------------------- Colleagues I have solved the miscoding with subscript and groups in panel.superpose. I was neglecting to pass in the variables correctly. "sardine.egg.T.S.space.2001.and.2002.exp" <- function() { library(lattice) library(grid) ##

I am trying to display data ion top of colored rectangle on the same levelplot. While using superpose the shape and symbol for levelplot changes to small circle. I am unable to figure what exactly I am doing wrong... It may be straightforward solution... .I will appreciate help to fix this issue.

I investigated why I was getting this error message... Error in Ops.factor(groups[subscripts], vals[1]) : Level sets of factors are different which led me to putting a browser in panel.superpose: Called from: panel.superpose(x, y, subscripts, ...) Browse[1]> vals vals [1] 1 2 3 Levels: 1 2 3 Browse[1]> groups[subscripts] groups[subscripts] [1] 1 2 3 1 2 1 2 3 1 2 3 1 2 3 Levels: 1 2

Dear R-helpers, the problem I'm facing today is to convince lattice to paint some areas in gray. The areas I would like to have in gray, are confidence bands I've googled around in the mailing list archives and eventually find some clues. This link is my starting point http://tolstoy.newcastle.edu.au/R/e2/help/07/04/15595.html I'm reproducing here the code for your convenience est

I am using the code example from the R graph gallery to look at a cloud plot: require(lattice) data(iris) print(cloud(Sepal.Length ~ Petal.Length * Petal.Width, data = iris, groups = Species, screen = list(z = 20, x = -70), perspective = FALSE, key = list(title = "Iris Data", x = .15, y=.85, corner = c(0,1), border = TRUE,

Hello everyone I have dataset containing a monetary value (ABS) and two factors (Fct, Group). I am able to create useful using: bwplot(ABS~Group|Fct) and dotplot(ABS~Group|Fct) Question: What do I have to do to overlay the dotplot with the bwplot (same data set)? I've found a couple of posts that hinted at the possibility of doing that, and checked the panel.superpose() help, but the info

Hello everyone I have dataset containing a monetary value (ABS) and two factors (Fct, Group). I am able to create useful using: bwplot(ABS~Group|Fct) and dotplot(ABS~Group|Fct) Question: What do I have to do to overlay the dotplot with the bwplot (same data set)? I've found a couple of posts that hinted at the possibility of doing that, and checked the panel.superpose() help, but the

Dear R users, I try to use xyplot() to display two different response variables from the same dataframe per panel, but don't succeed: xyplot(ptot.seaslog ~ vmcwit | seas, data=reeks, as.table=TRUE, panel = function(x,y){ panel.xyplot(x, y, ylim=c(0,1)) panel.superpose(x=reeks$vmcwit, y=reeks$ptotbin, panel.groups = "panel.xyplot",

Hi All, I am trying to understand panel functions. Let's use this example. library(lattice) time<-c(rep(1:10,5)) y <-time+rnorm(50,5,2) group<-c(rep('A',30),rep('B',20)) subject<-c(rep('a',10),rep('b',10),rep('c',10),rep('d',10),rep('e',10)) myData <-data.frame(subject,group,time,y) head(myData) Plot 1 xyplot(y ~ time

I would like to be able to use lme to fit random effect models In which some but not all of the random effects are constrained to be independent. It seems as thought the pdMat options in lme are a promising avenue. However, none of the existing pdMat classes seem to allow what I want. As a specific example, I would like to fit a random intercept/slope mixed model to longitudinal observations in

Dear R-ers, In my question there are no statistics involved - it's all about data manipulation in R. I am trying to write a code that should replace what's currently being done in SAS and SPSS. Or, at least, I am trying to show to my colleagues R is not much worse than SAS/SPSS for the task at hand. I've written a code that works but it's too slow. Probably because it's

Hi everybody, using bwplot for producing panel boxplot with 3 dimensions i want to add a mark on each boxplot representing one individual (on all its dimensions) till now, i didn't succeed getting the desired solution I want as well to keep the median symbols as a line Many thanks for your help christophe here is the tested code: ######################## library(lattice) ex <-