similar to: multiple density plot

Hi! I have used the following command: densityplot(~PV1CIV, groups=SGENDER, data=ISGFINC2, lwd=2, col=1, lty=c(1,2), pch=c("+","o"), key=list(text=list(lab=levels(ISGFINC2$SGENDER), col=1), space="bottom", columns=2, border=T, lines=T, lwd=2, lty=c(1,2), col=1), ref=T, plot.points=F) to produce a lattice density plot presenting the distribution of

Dear R-help listers, Under the helps from the ggplot2 list, I have set up method of drawing a graph with multiple density plots arranged one by one in one page. Now, I want to add 95% confidential interval as vertical lines to x axe in density plot. I have found the library(hdrcde) can do this work, but I do not know how to handle functions of this library when I used ggplot2 to draw the graph.

Dear R-help listers, I want to add 95% confidential interval as vertical lines to x axe in density plot. I have found the library(hdrcde) can do this work, but I do not know how to handle functions of this library when I used ggplot2 to draw the graph. Thank you in advance. The data and codes followed: # dummy data factor<-rep(c("Alice","Jone","Mike"),each=100)

Hello, I would like to be able to plot an array on a plot, something like: |arg1 | arg2 | arg3 val1| 0.9 | 1.1 | 2.4 val2| 0.33 | 0.23 | -1.4 val3| hello| stop | test I know Rwave is good to report but don't want to use it. ? Is there a package that allow quick and dirty plot of dataframes like this ? Thanks a lot -- View this message in context:

I am using the following commands for plotting kernel density for three kinds of crops density(s22$Net_income_Total.1, bw="nrd0",adjust=1, kernel=c("gaussian"))->t plot(t, xlim=c(-30000,40000), main="Net Income Distribution", axes=F, ylim=c(0,0.00035). xlab="Value in Rupees") par(new=T) density(s33$Net_income_Total.1, bw="nrd0",adjust=1,

Dear R users: I have a dataset with two variables (>20000 observations, two samples from same subject) and I used "kernSur" from library(Genkern) to get a estimated bivariate density and corresponding plots as follows: new.data.normal<-data.normal[!is.na(data.normal[,2]),] x<-new.data.normal[,2] y<-new.data.normal[,3] op <- KernSur(x,y, xgridsize=50, ygridsize=50,

Hi! I have a problem with Kernel density estimate plot for 3-dimensional data in ks-package. Here the example: # load ks, spatstat # three-dimensional kernel density of B B <- pp3(runif(300), runif(300), runif(300), box3(c(0,1))) x <- unclass(B$data)$df H <- Hpi(x) fhat <- kde(x, H=H) plot(fhat) plot(fhat, axes=FALSE, box=FALSE, drawpoints=TRUE);

Hello all, I looking at package dse or vars or mAr I know how to simulate a VAR(p) process, my problem is that most of those processes are unstable (not weakly stationary). Do anybody know how to generate a random VAR (or VARMA even better) process that is weakly stationary? Thanks -- View this message in context: http://r.789695.n4.nabble.com/simulating-stable-VAR-process-tp4261177p4261177.html

Hello, I have a data.frame and I want to transfor it in a list of rows or columns. I can do apply(myDataFrame,MARGIN=1,FUN=???) I remember that there is a function which mean return or access column ... something like "::" or "]," or "[," I can't remember can somebody refresh my memory? -- View this message in context:

Hi, in order to save space for a publication, it would be nice to have a combined scatter and density plot similar to what is shows on http://addictedtor.free.fr/graphiques/RGraphGallery.php?graph=78 I wonder if anybody perhaps has already developed code for this and is willing to share. This is the reproducible code for the histogram version obtained from the site: def.par <-

I want to create a 3d plot with densities. I use the function density to first create a 2d dimensional plot for specific x values, the function then creates the density and puts them into a y variable. Now I have a second set of x values and put it again into the density function and I get a second set of y variables and so on.... I want to put those sets into a 3d plot, I hope you know what I

I've got a few issues with the x-axes in the histogram and density plots. First, often the default x-axis doesn't even extend to the length of my data. R often draws histogram bars (or density lines) farther than the drawn x-axis extends. For example, I might have a histogram bar at -15,000. But I wouldn't know that, because the most negative number on the x-axis is -10,000. The

Hi, there. Suppose I have a bivarariate data matrix y1 and y2. I want to plot a 3-D picture of the estimated density f(y1, y2) against y1 and y2? How can I do that? Do I use persp() or density()? Thanks for your help. Yulei $$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$ Yulei He 1586 Murfin Ave. Apt 37 Ann Arbor, MI 48105-3135 yuleih at umich.edu 734-647-0305(H) 734-763-0421(O) 734-763-0427(O)

Hi, When R generates density plots and these are exported to postscript( a=matrix(1:100,10,10);image(a,col=rainbow(100);dev.copy2eps(file="image.eps") ) The result often looks bad when rendered on screen. The help page states that this is because programs use anti-aliasing. That seems to be true - turning off anti-aliasing for gs (-dGraphicsAlphaBits=1) of in OSX's preview makes

I'm trying to shade part of a density plot. The code I'm trying (using the Old Faithful data as an example) is something like this: # The Old Faithful geyser data data(faithful) d <- density(faithful$eruptions, bw = "sj") plot(d) polygon(d[d$x>4], col = "wheat") I expected that the part of the curve to the right of 4 on the x axis should be shaded, but nothing

Hi everyone, I'm trying to plot density curves on the axes of a plot, in a similar way to the 'rug' function. I have had a look at a few approaches and libraries, including: * layout http://addictedtor.free.fr/graphiques/RGraphGallery.php? graph=78 * fancygraph http://addictedtor.free.fr/graphiques/RGraphGallery.php? graph=81 * ggplot - gave up since it needs R 2.3.0 and

Good Evening- I have a set of nine scenarios I want to plot to see how the distribution is changing, if one tail is getting larger in certain scenario, currently I am using this code colnames<-dimnames(sag_pdfs)[[2]] par(mfrow=c(3,3)) for(i in 1:9) { d<-density(sag[,i]) plot(d,type="n", main=colnames[i]) polygon(d,col="red",border="grey")} where sag is

Hi, Forgive me, because I am new in R. I need a graph, where: - y axe has log scale - graph would have 4 set values: set first (out$a) has values over 5.5, set second (out$b) and third (out$c) has values over 0.005 and the last set (out$d) has values over 0.0005 of y axe. For this reason, I need have log scale on y axe. I've look for web, but I can't do the graph that I need. I try to do

Hello, I am looking for a good and detailed documentation about Sweave... but can't find anything more that 15 pages asking Google... Any hint on that point ? Cheers Colin -- View this message in context: http://r.789695.n4.nabble.com/Good-documentation-about-Sweave-tp2714326p2714326.html Sent from the R help mailing list archive at Nabble.com.

Dear all. I have to plot a the marginal population density for a heat map that represents the population density of a city. I have been able to plot the heat map in the lower left corner, the marginal density in x in the upper left corner and the marginal density in y in the lower left corner. What I need is to change this plot to include the marginal density in the diagonal direction of 135