similar to: Lattice 3d coordinate transformation

Hello list! I am trying to project the fitted surface to a 3d plot of the data, similar to figures 13.7 or 6.5 in Deepayan Sarkar's "Lattice, Multivariate Data Visualization with R", but replace the contour/map lines with "levelplot". Problem is I can't get the color regions to line up after the coordinate transformation. Is there a simple solution my geometry

Hello folks, i'm a R beginner and i want to put in a same plot both contour lines and persp plot. For example, fn<-function(x,y){sin(x)+2*y} #this looks like a corrugated tin roof x<-seq(from=1,to=100,by=1) #generates a list of x values to sample y<-seq(from=1,to=100,by=1) #generates a list of y values to sample z<-outer(x,y,FUN=fn) #applies the funct. across the combos of x

Good morning gentlemen! I'm not a fan of the lattice due to a large number of procedures what should be done to reach a simple goal, but have confess that in some cases the graphics are way better than the graphics. Some days I have been searching without success as is to add a cut-off point on a graph of response surface. It is interesting that the researcher to look at the graph spotting

Hello R Users, How to make a variable equidistance with time i.e. how to interpolate a variable if it is not sampled at equal time interval. Many thanks, Regards, Yogesh [[alternative HTML version deleted]]

Hi, I've got a matrix, Z, of values representing (as it happens) optical power at each pixel location. Since I know in advance I've got a single, convex peak, I would like to do a 2D parabolic fit of the form Z = poly((x+y),2) where x and y are the x,y coordinates of each pixel (or equivalently, the row, column numbers). Is there an R function that lets me easily implement that?

Hi, Suppose I have a multivariate response Y (n x k) obtained at a set of predictors X (n x p). I would like to perform a linear regression taking into consideration the covariance structure of Y within each unit - this would be represented by a specified matrix V (k x k), assumed to be the same across units. How do I use "lm" to do this? One approach that I was thinking of

I'm trying to make a set of contour plots of bivariate kernel density estimates, showing three such plots overlaid, similar to this plot http://euclid.psych.yorku.ca/SCS/Private/Test/ridge-boot2.pdf except that I would like to have the contours *filled* (using transparent colors). To make this reproducible, I've saved the results of KernSmooth::bkde2D() in the following file:

Dear expeRts, I would like to add two points to a wireframe plot. The points have (x,y,z) coordinates where z is determined to be on the wireframe [same z-value]. Now something strange happens. One point is perfectly plotted, the other isn't shown at all. It only appears if I move it upwards in z-direction by adding a positive number. So somehow it disappears in the wireframe-surface

Hi, I'm trying to follow the suggestions given by Deepayan Sarkar in this message: http://tolstoy.newcastle.edu.au/R/help/05/11/16135.html to plot 3-D points on a wireframe plot. The problem is that I keep getting a partly formed plot- with the colored lattice visible but no axis labels or additional points- with the error message "error using packet 1, 'x' and 'units'

Greetings, I have what I hope is a simple question. I would like to change my contour interval on the vis.gam( plot.type="contour") in the mgcv package. Is this a situation where I need to modify the function or is there a default value I can change? Thanks

Hi, I'd like to compare SST data for year 2000 with SST for year 2001. I managed to get filled contour plots showing monthly SST for both years (12 plots for each year, 24 plots in total). In order to compare year 2000 and year 2001, however, I'd need to have the same legend scale (same color bar) in both years plots. Thus, my question is: is there a way to set the legend scale in

Hello all, I’m trying to add some data points to a wireframe. X an Y axis are independent variables, Z axis is predicted probability. I’d like to add the original data points on which the predicted probabilities are based to the wireframe. I’ve followed some of the previous post on this but get stuck : ## first part yields the wireframe## setwd("C:/Temp") rnp <-

Hi all, I'd like to plot a set of data (x,y,z) as 3D-cloud, and add several line plots to the same 3D graph: Two questions: 1) How do I connect points to get a line? > cloud(z~x*y,data=d,zlim=c(0,1)) # works > cloud(z~x*predict(l),data=d,zlim=c(0,1),type="l") # type="l" doesn't Warning message: type = l not implemented, consider using

Dear R help contributors, I'd like to plot ground temperature with time on X-axis and depth on Y-axis on this datasets ( http://r.789695.n4.nabble.com/file/n3301033/NEdaily.csv NEdaily.csv ), and to do so I use the following commands: library(RSEIS) xNE <- seq(1, as.numeric(as.Date(max(NEdaily[[1]])) - as.Date(min(NEdaily[[1]]))), 1) yNE <- rev(c(-0.3, -0.5, -0.7, -0.9, -1.1,

Dear R community, I have one problem with figures. I draw the Relative Distribution graph, it looks like barchart(X,Y plot), but I have ten(year) Relative Distribution grapgs, have any command am can combine ten barcharts(X,Y plot) to become a three dimensions barchart(X,Y,Z plot)? All help highly appreciated Best, Yichih One Relative Distribution graph:

Rers: I can't seem to locate the command to suppress what appears to be a faint internal grid when running the following command to make a filled contour plot of some data I have (x,y,z being the inputs):

Dear all, As a newbie in R I would like to do the following (simple?) thing: to plot a filled.contour plot over a map showing country boundaries (e.g. for Europe) What i do is: map('worldHires',xlim=c(-10,40),ylim=c(35,70),boundary = TRUE,border=0.1) map.axes() filled.contour(mslp, zlim=c(1000,1020),color.palette = colorRampPalette(c("blue", "white",

Here is another, perhaps trivial, plotting question. I am making a filled contour plot and have almost everything dialed in the way I want it. The last hurdle (that I can foresee) is adjusting the look of the key. I'm plotting the 25%, 50%, 75%, and 95% quantiles and I want the key to be evenly spaced, e.g., the width of the 25% and the 95% should look the same on the key. They are labeled

Hi, I am using function wireframe from package lattice to draw a 3D surface. I would like to add a few points on the surface. I read in a post from Deepayan Sarkar that "To do this in a wireframe plot you would probably use the panel function panel.3dscatter". Does someone have an example? When calling panel.3dscatter with only x, y and z arguments I get "argument

Hello list, I just started R today and tried something quite simple. I wanted to create a colored plot and eventually after hours of fiddling around got it working. However, my solution seems very suboptimal and I'd really appreciate your hints on how to improve. I believe that R already offers many functions I coded (e.g. distance between two vectors, vector length, vector normalization and