similar to: Strange behavior in Lattice when superimposing

Dear People, I have a data set of data x from a probability distribution, and I have a function, mydensity, of the pdf of that distribution. I'm asking for help in superimposing the histogram of x and the plot of mydensity. In the function below, I call truehist and curve, but these are plotted in different figures. I'd like them to be plotted on the same figure, and to use common

Hi I would like to superimpose group-specific densityplots on top of an overall histogram using panel.histogram and panel.densityplot. Furthermore, I would like to automatically adjust the range of the y-axis to take into account the ranges of both histogram and densityplot. This last part is where I have a problem. I believe using the prepanel argument of histogram is typically the way to go,

Is there any function like par(new=T) for lattice. I want to plot a histogram in percentages on the right hand side and also superimpose the densityplot with its density scale on the lhs. so far I am only able to do this histogram( temp[,2]~ temp[,1],nint=100,type="desnity", xlab = "Population Size", panel = function(x, ...) {

Given a data frame of a categorical variable and two continuous variables, I would like to display one continuous variable against the other for each value of the categorical variable, all superimposed on the same plot. For example: data(Indometh); str(Indometh) Classes 'nfnGroupedData', 'nfGroupedData', 'groupedData' and 'data.frame': 66 obs. of 3

I'm trying to use a lattice function within a function and have problems passing the "groups" argument properly. Let's say I have a data frame d <- data.frame(x = rnorm(100), y = c("a", "b")) and want to plot variable x in a densityplot, grouped by the variable y, then I would do something like densityplot(~ x, d, groups = y) If however I wanted to

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

Hi All, I'm trying to add a 'rug' representation of my data to a plot created with densityplot(). While I can do this in the simple case, I can't do it properly when I include the "groups" argument. I have an example below. I am running a reasonably new version of R. print(sessionInfo()) R version 2.12.0 Patched (2010-11-07 r53537) Platform: i686-pc-linux-gnu

Hello, I'm doing some graphics for a paper and a need customize such with filled region above the density curve. My attempts I get something very near what I need, but I don't solve the problem of use semitransparent filled. Below a minimal reproducible code. Someone has any idea? require(lattice) # toy data... dt <- expand.grid(A=1:2, B=1:3, y=1:50) dt$y <- rnorm(nrow(dt), dt$B,

I wrote some code to do this. It only works with 2 groups (that's all I needed), but could probably be generalized. It got my graph made, and I haven't needed a graph like this one again, so I never went back to really clean it up. It works by first plotting both sets of rectangles, then going back over the ones that had the first bar totally covered by the second. Hope this helps,

Using one numeric and 2 factor variables densityplot( ~ Numeric | Factor1, ...) densityplot( ~ Numeric | Factor2, ...) .. both work, but densityplot( ~ Numeric | Factor1*Factor2, ...) produces the error Error in if (!(lo <- min(hi, IQR(x)/1.34))) (lo <- hi) || (lo <- abs(x[1])) || : missing value where logical needed None of the variables contain missing values. Any ideas

I am trying to plot two density lines on the same graph. Using the functions on the base package, I would go: plot(density(x), col = 1) lines(density(y), col = 2) And I get two distinct (one-bump) density lines. When I try to do it using lattice, I get two two-humped lines. (In other words, I think the smoothing function is taking the next set of data points and smoothing them in the same

Dear all, I have a undirected network (g), representing all the sexual relationships that ever existed in a model community. I also have a directed edgelist (e) which is a subset of the edgelist of g. e represents the transmission pathway of HIV. Now I would like to superimpose the picture of the sexual relationships with arrows in a different colour, to indicate where in the network HIV was

Dear R-help, I am creating a two lattice plots (a densityplot() and xyplot()) that have the same x-axes and then 'printing' them onto the same page, one above the other (see end of email for an example to generate the graph). With different labels on the y-axis for each plot the left spacing is different, and the x-axes don't align vertically. Although I can manually modify the

Suppose you have the following code: ########## Start code########## data(Chem97, package="mlmRev") densityplot(~gcsescore | factor(score), groups=gender, data=Chem97, auto.key=TRUE, plot.points=FALSE, ref=TRUE, panel=function(x,...){ panel.densityplot(x,...) median.values <- median(x)

Hi, I have two data sets; one is a population and the other a sample of that population. I am trying to plot both on the same trellis display. # Example data set with two numerical attributes and two categorical pop <- data.frame(var1=rnorm(2000, 2000, 500), var2=rnorm(2000, 2000, 500)) cat<-(runif(2000)<=.5)+0 for(i in 1:length(cat)){ if(cat[i] == 0){ pop[i,"cat1"] =

#After spending the entire day working on this question, I have decided to reach out for support: #I am trying to overlay a densityplot from one data set over a histogram of another, if I were to plot the two individually, they would look like: # data frame construction data.frame.A <- data.frame(rnorm(12*8), c(rep("one", 4), rep("two", 4), rep("three", 4)),

Searched archives and found some old email threads on the topic. But mot exactly what I think I need. Suppose I have a datafile such as tmp. tmp <- data.frame(var1 = c(rnorm(1000), rnorm(1000, 1, 1)), var2 = gl(2, 1000)) I'd like a plot similar to the one below, but with an abline of v=0 in the lower panel and v=1 in the upper panel. Code below creates two lines in each panel, not quite

Hello, I am try to make a density plot where plots are stacked like the one found here: http://dsarkar.fhcrc.org/lattice/book/images/Figure_14_03_stdBW.png I am facing problems, however. Using the code example below, I'd like to generate a separate panel for each val of id2. Within each panel, I'd like to have individual histograms each on separate lines based on the value of id1. ?Note

Hi, I've got a lattice xyplot and I want to superimpose correlation coefficients and p values on each panel. I've been trying to get this to work using something of the form: x <- rnorm(400) y <- rnorm(400) a <- gl(4, 100) xyplot(y~x | a, panel=function(x,y, ...){ panel.xyplot(x,y, ...) curr.cor <- cor.test(x,y) crho <- round(curr.cor$estimate,2)

Earlier, I posted the following question: I want to superimpose histograms from three populations onto the same graph, changing the shading of the bars for each population. After consulting the help files and the archives I cannot find out how to do this (seemly) simple graph. To be clear, I want - a single x axis (from -3 to 18) - three groups of bars forming the histograms of each population