similar to: Objects within environment

I have 2 vecros : x<-c(100,96,88,100,100,96,80,68,92,96,88,92,68,84,84,88,72,88,72,88) x1 = sample(x, 5, replace=FALSE) Now i want to get remaining values of vector "x" those are not member of vector "x1". Can anyone please tell me how to do that?

Thanks David, It is working. Holtman's also gave me a solution but, I wanted to have a color pallet for description of colors, that was not in his solution. However I need one small modification. If I want to plot only lower diagonal elements of 'dat' then how should I proceed? What I want is, to visualize only lower diagonal elements and having the color pallet on them only. Also

I'm trying to find a good way of attaching a list within a function such that the attached variables (the list's members) precede the global environment (.GlobalEnv) in the search list. Here is a non-working example using attach(), which hopefully explains better what I'm trying to do: > foo <- function(x=0, input=list(a=10)) { + attach(input) + on.exit(detach(input)) +

Dear all, I have following 2 zoo objects. However when I try to merge those 2 objects into one, nothing is coming as intended. Please see below the objects as well as the merged object: > dat11 V2 V3 V4 V5 2010-10-15 13:43:54 73.8 73.8 73.8 73.8 2010-10-15 13:44:15 73.8 73.8 73.8 73.8 2010-10-15 13:45:51 73.8 73.8 73.8 73.8 2010-10-15 13:46:21 73.8 73.8 73.8 73.8

Let me take an artifical matrix : dat = matrix(rnorm(200*200), 200, 200) My goal is to visualize this matrix according to the procedure, described in previous mails. I took Mendelssohn's advice and got following advice : ?plot.im Z <- setcov(owin()) plot(Z) .................... etc However I can not reproduce this example in my problem. How I can change my data

I've run into a scoping problem in R. I'm calling a function that * creates a formula * calculates a weight vector * calls lm with that formula and weights This fails. Here's a simplified reproduce example: # f works, g doesn't, h is a workaround rm(w) data <- data.frame(y=runif(20), x=runif(20), z=runif(20)) f <- function(k){ w <- data$z^k coef(lm(y~x, data

Dear all R users, I have a small doubt about panel data analysis. My basic understanding on Panel data is a type of data that is collected over time and subjects. Vector Autoregressive Model (VAR) model used on this type of data. Therefore can I say that, one of statistical tools used for analysis of panel data is VAR model? If you clarify my doubt I will be very grateful. Thanks and regards,

aDear list, I'm aware of the fact that I posted on something related a while ago, but I just can't sweat this off and would like to ask your for an opinion: The problem: Namespaces are great, but they don't resolve certain conflicts regarding name clashes. There are more and more people out there trying to come up with their own R packages, which is great also! Yet, it becomes

[My previous message rejected, therefore I am sending same one with some modification] I have 3 vectors with object name : dat1, dat2, dat3 Now I want to create a loop, like : for (i in 1:3) { cat(sd(dati)) } How I can do this in R? Regards,

Dear R list members, I'm encountering a problem with expand.model.frame(): Suppose that I define the following simple function (meant just to illustrate the problem): > fun <- function(model){ + expand.model.frame(model, all.vars(formula(model))) + } > and I have the following model, created with an explicit data argument: > mod Call:

I've noticed the following oddity where capture.output() prevents eval() from evaluating an expression in the specified environment. I'm not sure if it is an undocumented feature or a bug. It caused me many hours of troubleshooting. By posting it here, it might save someone else from doing the same exercise. Start by defining foo() which evaluates an expression locally in a given

Hello. What happens in the following is that I create two simple functions, f and g, on the workspace. Then I replace g. When I then call f, it uses the old version of g. Now clearly, the circumstances for this to happen must be quite special and rare. But I'd say they're not pathological. It seems to require two things: 1) masked versions of f and g on a search position lower down the

hi, hi, good morning everyone. I have a time series with binary outputs like : 0001011110100.................etc. Now I want to forecast the future values of that. Can anyone please tell me whether there is any tools exist in literature for dealing with this kind of binary observation? If possible please provide me some good references in net as well. rgd, Megh

Hi, I have following kind of dataset (all are dates) in my Excel sheet. 09/08/08 09/05/08 09/04/08 09/02/08 09/01/08 29/08/2008 28/08/2008 27/08/2008 26/08/2008 25/08/2008 22/08/2008 21/08/2008 20/08/2008 18/08/2008 14/08/2008 13/08/2008 08/12/08 08/11/08 08/08/08 08/07/08 However I want to use R to compile those data to make all dates in same format. Can anyone please tell me any automated way

I have following " 1975 01 7711.16" Here I need to identify where the <space> is there and then concatenate rest of the digits without <space>, i.e. I want to have "1975017711.16". Is there any R function? Regards,

I have following dataset: > res [,1] [,2] [,3] [1,] 1946 4 1.27 [2,] 1946 5 1.27 [3,] 1946 6 1.27 [4,] 1946 7 1.27 [5,] 1946 8 1.52 [6,] 1946 9 1.52 [7,] 1946 10 1.52 [8,] 1946 11 1.52 [9,] 1946 12 1.62 [10,] 1947 1 1.62 [11,] 1947 2 1.62 [12,] 1947 3 1.62 [13,] 1947 4 1.87 [14,] 1947 5 1.87 [15,] 1947 6 1.87 Now I write following code

I used ?image function to do that, like below : require(grDevices) # for colours x <- y <- seq(-4*pi, 4*pi, len=27) r <- sqrt(outer(x^2, y^2, "+")) image(x, y, r, col=gray((0:32)/32)) However my next problem to add a color pallet for color description [as shown in following link]. If anyone here tell me how to do that, it will be good for me. Regards, Megh Dal

Dear all, Please forgive me if there is a duplicate post; my previous mail perhaps didnt reach the list....... Let say I have following time series library(zoo) > dat1 <- zooreg(rnorm(10), start=as.Date("2010-01-01"), frequency=1) > dat1[c(3, 7,8)] = NA > dat1 2010-01-01 2010-01-02 2010-01-03 2010-01-04 2010-01-05 2010-01-06 2010-01-07 2010-01-08 2010-01-09

I have drawn a 3D scatter plot : library(mnormt) library(scatterplot3d) dat = cbind(rmnorm(3, rep(0,2), diag(2)), 1:3) scatterplot3d(dat) Now I want to do 2 things : 1 : In the Z-axis (i.e. height), I want to see only numbers 1,2,3, etc NOT, 1,1.5,2,2.5............. 2. I want to add two Horizontal planes at hight z=2 and z=3. Those two planes should look like "bottom" of that 3D plot

Dear all R users, Please forgive me if my question is too trivial. Suppose I have two variables, (x,y) which is log-normally distributed with expected value (mu1, mu2) and some variance-covariance matrix. Now I want to draw a random sample of size 1000 from this distribution. Is there any function available to do this? Thanks and regards, Megh