similar to: Mistake with contour...

R- Users: Can someone indicate what I am during wrong? This is a script essentially from Venerable & Ripley's text on interpolating a surface with loess function but I can not get it to run. Thanks. John Lewis Professor McGill University Montreal library(MASS) library(modreg) data(topo) par(mfcol=c(2,2), pty="s") topo.loess <- loess(z ~ x * y, topo, degree=2,

Hi Folks, I'm probably overlooking some small point, but can't see it. Trying the "Local trend surfaces" example from p.437 of MASS (3rd edn) by V&R, all goes well until the line contour(topo.mar$x, topo.mar$y, topo.lo$fit, levels=seq(700,1000,25), xlab="fi t", ylab="") which produces the response: Error in contour.default(topo.mar$x,

Hi, I was wondering if anyone knows of a way by which one can estimate values from a contour plot created by using the loess function? I am hoping to use the loess contour plot as a means of interpolation to identify the loess created values at points at pre-defined (x,y) locations. Could anyone point me in the right direction please? Thanks. Laura Quinn Institute of Atmospheric Science School

If a run a LOESS model and then produce a smoothed surface: Is there any way to determine the coordinates of the local maxima on the surface? [[alternative HTML version deleted]]

I am trying to create a topographic map of an island - the filled.contour function works fine except i am experiencing difficulty trying to represent the sea properly. Basically I want the default colour blue for any instance where z=0, if I simply use the default topo.color I get shades of blue for z values up to 220 metres. Is there a way in which I can specify terrain.color for all values of

Although the 'spatial' documentation doesn't mention that extractAIC works, it does seem to give an output. I may have misunderstood, but shouldn't the following give at least the same d.f.? > library(spatial) > data(topo, package="MASS") > extractAIC(surf.ls(2, topo)) [1] 46.0000 437.5059 > extractAIC(lm(z ~ x+I(x^2)+y+I(y^2)+x:y, topo)) [1]

Dear all, I wonder about what could actually be possible with the function "contour": 1/ - the definition of contour lines is most often meaningless when the contours are drawn in areas where no real data points exist. It can however happen that irregular distributions lead to more or less irregular clouds of data points. Interpolations (eg: loess regression, GLM, etc...) are however

Hi all, I'm trying to make multiple lattice contour plots which have the same color key, to allow good comparisons. However, I run into some problems when fitting the plots to the color key. Basically my strategy to tackle this problem was: 1) define a color key for all plots; 2) calculate the variable range for each plot; 3) calculate the range of colors from the color key that correspond

Dear All, I was looking for the color index in?image function,?such as from topo.colors(n) and etc. but still never found it. For instance, from the help menu. ########################################### # Volcano data visualized as matrix. Need to transpose and flip # matrix horizontally. image(t(volcano)[ncol(volcano):1,]) # A prettier display of the volcano x <- 10*(1:nrow(volcano)) y

Context: Windows XP, R 1.8.1 I'm studying Venables-Ripley "MASS" book and having a go at the many examples in library MASS. The code I'm checking (from script ch04.R) now is ...... data(swiss) splom(~ swiss, aspect = "fill", panel = function(x, y, ...) { panel.xyplot(x, y, ...); panel.loess(x, y, ...) } ) which produces an agreable plot with a gray

Dear List, Is there a color palette avaliable similar to what is used in satellite ocean color imagery? I.e. a gradient with blue on one end and red on the other, with yellow in the middle? I have tried topo.colors(n) but that comes out more yellow on the end. I am looking for something similar to what is found on the CoastWatch web page:

I'm trying to find a way to fit a polynomial of degree n in x and y to a set of x, y, and z data that I have and obtain the coefficients for the terms of the fitted polynomial. However, when I try to use the surf.ls function I'm getting odd results. > x <- seq(0, 10, length=50) > y <- x > f <- function (x, y) {x^2 + y} > library(spatial) > test <-

Hi all, I have the following -newbye- problem. Inside R, I am trying to process a file and creating from it many files. The file is organized in different columns, the second containing a code. I want to create as output objects, which contain only entries in a certain code range, and whose name contain the code itself. Here is my attempt indice <- (201:399) for(i in indice){ data.i <-

Dear useRs, I got stuck trying to generate a palette of topographic colors that would satisfy these two requirements: - the pallete must be 'anchored' at 0 (just like on a map), with light blue/lawn green corresponding to data values close to 0 (dark blue to light blue for negative values, green-yellow-brown for positive values) - the brown must get darker for higher positive

Hi all, I'm trying to generate a grid of four plots. The first 2 appear just fine, but the final 2 will not appear in the grid, instead overwriting the first two. Any ideas on how to get them all in the same window would be greatly appreciated. Cheers, Jonathan library(fields) par(mfrow=c(2,2)) #2x2 plot windows plot(c(2,4),c(2,2)) # works fine plot(c(2,4),c(2,2)) # works fine

I'm learning R from scratch on my linux box, being deeply biased at work by those graphical programs, nice to look but often poor in content and almost generally limited, running under M$ Windows. I wonder if someone out there can suggest to an absolute beginner as I am where to find a collection of examples of R-code (or Splus, as I understand) to play with in order to learn R quicker. The

I have a huge dataset(15k X 18) and tried to use the heatmap in R to examine the patterns. However, I found that heatmap and heatmap.2 gave me completely different outputs. Here are the codes: ------------ > dim(as.matrix(data.dcpm)) [1] 15462??? 18 > > heatmap(as.matrix(data.dcpm), col=topo.colors(100)) > heatmap.2(as.matrix(data.dcpm), col=topo.colors(100), key=TRUE,

In the text file pressione2008.csv I have the following "Data","MAX","MIN","Note" "07-01-2008 08:00:00", 135, 90, "Eccessi feste, inizio dieta" "07-01-2008 18:00:00", 135, 85, "" "08-01-2008 08:00:00", 125, 75, "" which is a collection of blood pressure data at different time of the day. I would

Apologies for the mass mailing today! I am attempting to produce a contour plot for phsical data on a map matrix. I have a small number of data points which each has an (x,y) co-ordinate together with a corresponding value which I would like to cvreate a contour plot for. I have tried the following code: contour(data$x,data$y,data$value) but am told: Error in contour.default(data$x, data$y,

Can anyone please hazard a guess at an estimate for a poor old squirrel hunter with a Very Very Dumb Question? Is wine likely to be able to install and run any of the proprietary GPS-interfacing topo map programs (DeLorme, Garmin, Mapquest, et al.) at any roughly predictable future date? The season opens in three weeks, my GPS (Garmin's etrex vista) is full -- and it still contains road maps