similar to: How do I edit the x-axis on a time series plot?

hi everyone, so,first it seemed a trivial question to me, but since I could not find anybody being neither able to answer this question nor giving a short config example. after a few sleepless nights and exhausting all the reading and research. here I am sharing my problem with all of you, in the hope of some possible solution/sugestion. or is it that this is impossible?? below my

To anyone who can help: I have two brief questions concerning sapply. Following below is the code for my example. The two problems are described at the end of the code: site <- rep(2:6, each = 12) tillage <- rep(c(1,-1), each = 6, times = 5) carbon <- c(18.23, 16.06, 17.81, 16.07, 17.26, 17.08, 14.92, 15.88, 12.11, 14.23, 16.99, 13.57, 20.34, 20.3,

Hi, I'm having difficulties in the manipulation of the function table. Necessary to have access its elements and I am not obtaining. For example, if I have a data.frame with name "df" and make: t < - data.frame(table(df)) and later trying to make a comparison of the type t[1,1 ] < 0.1, generates an error of the type: [1] NA Warning message: "<" not meaningful for

I'm using the parameters "mfrow" and "mfg" to display some graphics(plots) at the same time. Although, because of the parameter "mfg", the parameter "bg" don´t change the background color. What can I do to solve this? Here is the code I'm using... ... i <- 1 for(j in 1:4){ for(k in 1:2){ limiares <-

How I make the below matrix | a^0 0 0 ... 0 | | a^1 a^0 0 ... 0 | | a^2 a^1 a^0 ... 0 | | . | | . | | . | | a^n a^(n-1) a^(n-2) ... a^0 | with no loops, where "a" is a constant? ======================================================================== C?zar de Freitas Depto. de Estat?stica - UFPE Recife - Pernambuco - Brasil

I am trying calculate a probability using numerical integration. The first program I ran spit out an answer in a very short time. The program is below: ## START PROGRAM trial <- function(input) { pmvnorm(lower = c(0,0), upper = c(2, 2), mean = input, sigma = matrix(c(.1, 0, 0, .1), nrow = 2, ncol = 2, byrow = FALSE)) } require(mvtnorm) require(adapt) bottomB <- -5*sqrt(.1) topB <-

Does anyone have any R code or suggestions on how to generate a population that follows a Neyman-Scott process? More specifically, I'd like to randomly generate both the parents and the children from Poisson distributions and the children locations from a bivariate normal onto an N by N grid. If the locations spill over outside the grid, then I'd like to reflect those locations back into

Selim Daoud wrote: > here''s an interesting status report published by Microsoft labs > > http://research.microsoft.com/research/pubs/view.aspx?msr_tr_id=MSR-TR-2005-166 That is the paper in which Jim Gray coined "Mean time to data loss". It''s been quoted here before. Sad note: Turing award winner Jim Gray has been missing now for two weeks, after he went

Hi guys, I''m new to Xen - in fact I haven''t installed it yet - wanted to find out a bit more before I test the waters. Here''s what I want to do: 1. I''m getting a new Intel Core duo laptop within a couple of days. I believe the core duo chips have Vanderpool technology so it shouldn''t be a problem getting Xen to run windows unmodified - is this

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