similar to: simplest possible xyz plot

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,

Can some kind person point out my error here? I'm trying to set up a grid for a countour plot of a likelihood function. > u <- rnorm(20,9.5,2.5) > # sample of size 20 from N(9.5,2.5^2) > loglik <- function(th1,th2) { + n <- length(u) + -(n/2)*log(2*pi*th2^2)-0.5*sum((u-th1)^2/th2^2) + } > x <- seq(4.5,14.5,len=50) > y <- seq(0.5,6,len=50) > f <-

Hi, I have a contour plot and I want to shade a polygon (the area below a line) but the polygon shading wipes out the contour lines. Does anybody know how to shade the polygon and still see the contour lines? Thanks. Jeff

I apologize for how basic a question this is. I am a Stata user who has begun using R, and the syntax differences still trip me up. The most basic questions, involving as they do general terms, can be the hardest to find solutions for through search. Assume for the moment that I have a dataset that contains seven variables: Pollution, Temp, Industry, Population, Wind, Rain and Wet.days. (This

Hi, I've been driving myself insane with this problem. I have a trellis plot of contours, and I want each level to have something like "z=value" for each one. I can get each one to say z, or each one to say the value (by using as.factor) but not both. Heres an artificial example to show what I mean (as my actual data set is much larger!) x<-c(1,2,3) y<-c(2,4,6)

BTW. I checked help page of contour and maybe it could mention a note about akima package or interp function. Petr ------- Forwarded message follows ------- From: Petr Pikal <petr.pikal at precheza.cz> To: "Abhinav Verma" <abhinav1205 at gmail.com>, r-help at stat.math.ethz.ch Subject: Re: [R] Reading xyz data from a file and plotting a

Dear, I have XYZ data available in a MySQL database. I get it out, can plot the data with the plot() function, load it into a geoR datastructure. But what I actually would like to do is a simple contouring of the data based on a no Kriging interpolation such as TIN based. I know the first thing I shold do is interpolate a full matrix for the region I have my points for, then contour should

I discover last week the R software statistics programm, I have a small questions, When we generate a bivariate normal distribution is it possible to plot the generate distribution. The second one if there is a code to generate a bivariate student distribution. If yes i would ask you gratefully a help. Thank you very much

Hello, I used the following codes to generate bivariate normal dependence structure with unit Frechet margins. Sigma <- matrix(c(1,.5*sqrt(1),.5*sqrt(1),1),2,2) # generate y <- mvrnorm(Nsam, c(0,0), Sigma) # random v <- cbind(pnorm(y[,1],mean = 0, sd = 1), pnorm(y[,2],mean = 0, sd = 1)) z <- cbind(-1/log(v[,1]),-1/log(v[,2])) z1 <- z[,1] z2 <- z[,2] And to

Hi List, I am trying to plot a grid with an overlayed height. I have a dataframe with four variables: x,y,gridvalue,height. The dataframe has 2.5mio observations (ie grid points), I assign colors through the gridvalue using map_color_gradient thus producing: x,y,gridvalue,height,gridcol as variables of the dataframe. The grid dimensions are 1253 x 2001 (=2507253 data points). My attempts with

Dear List, Suppose we have a variable K.JUN defined as (with 1=wet, 0=dry): K.JUN1984 = c(1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1) K.JUN1985 = c(0, 1, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1) K.JUN1986 = c(0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1)

Dear list, Is there anyway i can make the following formula short by r-programming? CYCLE.n<-c(NA, WET[1]*DRY[1], WET[1]*DRY[2]+WET[2]*DRY[1], WET[1]*DRY[3]+WET[2]*DRY[2]+WET[3]*DRY[1], WET[1]*DRY[4]+WET[2]*DRY[3]+WET[3]*DRY[2]+WET[4]*DRY[1], WET[1]*DRY[5]+WET[2]*DRY[4]+WET[3]*DRY[3]+WET[4]*DRY[2]+WET[5]*DRY[1],

Hello, I would be very grateful if someone could give me a hand with my split plot design problems. So here is my design : I am studying the crossed-effects of water (wet/dry) and mowing (mowed/not-mowed = nm) on plant height (PH) within 2 types of plant communities (Xerobromion and Mesobromion) : - Within each type of communities, I have localised 4 blocks - In each block, I have defined

Hi, Thanks for the quick reply again. > On Thu, Dec 15, 2011 at 1:17 PM, David Fang <fang at csl.cornell.edu> wrote: >> Hi, >> >> I've bootstrapped llvm/clang from svn-trunk on powerpc-darwin8 (g++-4.0.1), and >> have the following test results to share. >> Summary below, full log at: >>

Hello, this is a request for assistance that I submitted earlier, this time with the dataset. My mistake for taking up bandwidth. I've also rephrased the question to address an additional concern. I'm working on a windows XP machine with R 2.8.1 1). I'd like a barchart (or other lattice type display) HSI ~ of the three factors (Region, Scenario and HydroState). However

I have a problem with including extra data in a lattice graphic. I am trying to put some calculated values in an extra column of a boxplot. A minimal example should show what I am trying to do: foo <- data.frame( Treatment=rnorm(1:12,2),

Hello, I am trying to make a correlation matrix in R using cor() and also to get the p-value for each correlation using cor.test(). I can't get these commands to work. I'm getting errors like the following: cor(Pollution, Wet.days) Error in inherits(x, "data.frame") : Object "Wet.days" not found cor("Pollution", "Wet.days") Error in

Dear R list, I have a sequence of weekly observations of number of adults and larvae in various size classes from a butterfly population living in a subtropical area with pronounced wet and dry seasons. Wet and dry seasons are each defined 26 weeks long with fixed start and end dates. The data span 103 weeks (two seasons each of wet and dry) with some missing weeks. What I would like to do is

Hi all, I have a matrix simulating migration in a spatial model. I want to be able to define movement (the values of m1, m2 and m3) as only != 0 between adjacent patches and contingent on certain conditions as defined in the function. Here is the code: WET<-function(t) {everglades$precipitation[t]} #simply reads precipitation data from a csv, value is numeric AB<-function(WET,t)

Hi Lisp users, I'm a user of both Common Lisp and R (GNU R). I found R has a rich collection of statistical and numerical computation functions, while it is not as extensible as Lisp (Common Lisp). I considered Lisp-Stat but its only implementation is not in the usuall Common Lisp, and the available functions in CRAN are far richer than Lisp-Stat currently has. I want to know if there is