similar to: density plot - beginner's question

Dear All, I am trying to visualize the surface of a bivariate kernel density estimate. I have a vector of bivariate observations(x,y), and a function which computes the kernel density estimate z corresponding to each observation. I cannot generate the (x,y) data in the ascending order needed by persp(x,y,z). I was wondering whether there is an R version of the S function interp. Would anybody

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

Hi all, I'm fairly new to R, so I'm still trying to feel out what is available to me. I would like to be able to plot joint density in a two dimensional plot where density is indicated by color or darkness gradients, like a 2d color coded topographic map. Ideally, the output would be something I could then plot other points or lines on. Currently, I'm calculating joint density with

Dear All, I am trying to visualize the surface of a bivariate kernel density estimate. I have a vector of bivariate observations(x,y), and a function which computes the kernel density estimate z corresponding to each observation. I cannot generate the (x,y) data in the ascending order needed by persp(x,y,z). I was wondering whether there is an R version of the S function interp. Would anybody

Dear R users I have a data set which has five variables. One depenedent variable y, and 4 Independent variables (education-level, householdincome, countrygdp and countrygdpsquare). The first two are data corresponding to the individual and the next two coorespond to the country to which the individual belongs to. My data set does not make this distinction between individual level and country

I have so far used the following command glm(formula = s ~ age + gender + gemedu + gemhinc + es_gdppc + imf_pop + estbbo_m, family = binomial(link = "probit")) My question is 1. How do i discard the non significant selection variables (one out of the seven variables above is non-significant) and calculate the Inverse Mills Ratio of the significant variables 2. I need the inverse

I am typing the following on the command prompt: >variab = read.csv(file.choose(), header=T) >variab It lists 900,000 ( this is the total number of observations in "variab" ) minus 797124 observations and prompts the following message [ reached getOption("max.print") -- omitted 797124 entries ]] Is there a way to see the entire set of data, ie all of 900,000 obs, and

Hi Saurav! On Sun, Jul 12, 2009 at 6:06 PM, Pathak, Saurav<s.pathak08 at imperial.ac.uk> wrote: > I am new to R, I have to do a 2 step Heckman model, my selection equation is > below which I was successful in running but I am unable to proceed further, > > > > I have so far used the following command > > glm(formula = s ~ age + gender + gemedu + gemhinc + es_gdppc +

Hello I am trying to draw a basic black and white map of two European countries. After searching some key words in google and reading many pages I arrived to the conclusion that persp() could be used to draw that map. I have prepared three small example files, which are supposed to be the files required for running that function. xvector is a vector with the longitudes yvector is a vector with

hi, i am need to plot two or more sets of data in a 3d scatterplot, each set with different color. i tried Rcmdr, and the 3d scatterplot facility, based on rgl. that is what i need. but i cannot seem to code different sets of data differently. any help will be very helpful. i tried scatterplot3d, but it is difficult to get the right angle in it. i need to be able to rotate the axes, and

Hi, I need some suggestion on how I could modify the color on some rectangle that I have created using "image". In other words, I have a 5x5 matrix, say, m. m <- matrix(rnorm(25), nrow=5) I create a grid of rectangles by: image(m) Now I want to change the color of rectangle (3,3) to blue. I don't know how this could be done, and searching the web has

Dear R users, I would like to plot the bivariate density surface with its marginal densities on the sides of the 3D box, just like in the picture I attach. I tried to found information about how to do it but did not find anything. Does anyone know how to do it? Thanks in advance, Eduardo.

Hi I am using Stata 10 and I need to import a data set in stata 10 to R, I have saved the dataset in lower versions of Stata as well by using saveold command in Stata. My RAM is 4gb and the stata file is 600MB, I am getting an error message which says : "Error: cannot allocate vector of size 3.4 Mb In addition: There were 50 or more warnings (use warnings() to see the first 50)" Thus

Hi All, I have a 2-dim density defined on 0<x<1, 0<y<1, x<y. I know the exact formula of the density. How can I visualize it? What plot functions can I use? Thanks, Annie [[alternative HTML version deleted]]

Hello, I'm willing to plot a sequence of densities on a 3d graph, something like ----------------------------------------------------------------- x <- sapply(1:10, function(i)rnorm(1000)) f <- sapply(1:10, function(i)density(x[,i], from=-5,to=5)$y) grid <- density(x[,1], from=-5,to=5)$x win.graph() persp(grid1, 1:10, f,theta=-50, phi=30, d=2)

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, I guess I have a naive question. I use kde2d function in a standard way to estimate kernel densities of x and y (x and y are vectors) and plot them using image(). f1=kde2d(x,y) image(f1) But what if I want to see kernel estimates of three variables, x, y and z (a vector) plotted together ? Something in which x<->y is plotted and colored according to the corresponding value of z ?

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);

Hi people, Does anybody know some Density-Based Method for clustering implemented in R? Thanks, Fernando Prass _______________________________________________________

A student is trying to cluster some data. Tree-building things seem to be pretty hopeless (we've tried most of the ones in R, I think). Multi-dimensional scaling produces somewhat tantalising results: things do clump together somewhat, but the clusters overlap a lot. I was wondering if these was an artefact of squeezing it down to 2D, and whether 3D might be better. So loc <-