search for: 0.5

Hi all, I'm trying to filter data into respective numbers. For example, if the data ranges from 0 to <0.1, group the data. And so on for the rest of the data. There are inconsistencies in the output. For example, b1[[3]] lumps all the 0.2s and 0.3s together while 0.6s are not in the output. Running the function - table(f1) - shows that each of the components/numbers has x number of

hi guys i have multiple data frames which i want to merge. there are four of them..eg pdf SampleID UVDose_J RepairHours Day_0 Day_45 Day_90 1 SDM001 1.0 3 485.612 465.142 490.873 2 SDM001 1.0 3 503.658 457.863 487.783 3 SDM001 1.0 2 533.193 451.044 456.973 4 SDM001 1.0 2 538.334 452.887 474.915 5 SDM001 1.0

Hi there, I tried to add a few circles on an existing figure using the following codes grid.circle(x=0.5, y=0.5, r=0.1, draw=TRUE, gp=gpar(col=5)) grid.circle(x=0.5, y=0.5, r=0.3, draw=TRUE, gp=gpar(col=5)) grid.circle(x=0.5, y=0.5, r=0.5, draw=TRUE, gp=gpar(col=5)) points(0.5, 0.5, col = 5) # centre of the circle , but all circles moved away from the centre. Could we do any

Dear all, I'm having some problems getting my recursive function to work. At first I though that maybe my data was too big and I increase option(expressions=50000). Then I thought that I would try it on some smaller data. Still not working. :( I would have thought there should be a function for this already, so any suggestions are welcomed for other methods. I did try igraph but couldn't

I have a function like this: changedir <- function(dataframe) { dir <- dataframe$dir gc_content <- dataframe$gc_content d <- ifelse(dir == "-", gc_content <- -gc_content,gc_content <- gc_content) return(d) } The goal of this function is to be able to input a data frame like this: > lala dir gc_content 1 + 0.5 2 - 0.5 3 +

Hi- I am trying to create a table of values by adding pairs of vectors, but am running into some problems. The problem is best expressed by a simple example. Starting with a data table "basis": atom x y z 1 Cu 0.0 0.0 0.0 2 Cu 0.5 0.5 0.5 I want to add 0.5 0.5 0.5 (and also the 0 0 0 but it wouldn't change the values below so I won't refer to it in the rest

Hello, Using the dataset below I produce a soil.texture plot (R code for this included at the end). One will notice I have plotted the points based on whether or not they are in a region called 'upstream' or 'downstream'. I'm curious if there is a way to somehow extract counts of the number of points (red points and blue points) falling within each classification (e.g. silty

CentOS Errata and Bugfix Advisory 2013:1836 Upstream details at : https://rhn.redhat.com/errata/RHBA-2013-1836.html The following updated files have been uploaded and are currently syncing to the mirrors: ( sha256sum Filename ) i386: d390b1f7d615553c9275ced0f7706d1a914a6d5b1a4ee1d51947a1376981ad07 glx-utils-9.2-0.5.el6_5.2.i686.rpm

Hi all, I'd like to know, if I can solve this with a shorter command: a <- rnorm(100) which(a > -0.5 & a < 0.5) # would give me all indices of numbers greater than -0.5 and smaller than +0.5 I have something similar with a dataframe and it produces sometimes quite long commands... I'd like to have something like: which(within.interval(a, -0.5, 0.5)) Is there anything I

Hi all, I have two matrices: G<-matrix(c(2.0, 0.5, 0.5, 0.5, 2.0, 0.5, 0.5, 0.5,2.0),3,3) P<-matrix(c(1.0, 0.5, 0.5, 0.5, 1.0, 0.5, 0.5, 0.5,1.0),3,3) and I want to run this equation to get a new matrix F: F = [P+2G]^-1/2 P [P+2G]^-1/2 Could someone please tell me how to code this in R? Many thanks in advance for your time. Best wishes, Matt [[alternative HTML version deleted]]

Dear R and S People: I have run across something very strange. Here is a function that I wrote for R: boot1 <- function(y,method="f",p=1) { n1 <- length(y) n2 <- n1*p n3 <- n2 - 1 a <- 0.5*(outer(1:n3,1:n3,function(x,y){n2 - pmax(x,y)})) return(a) } and here is the R output: > y1 [1] 9 8 7 3 6 > source("boot1.R") > boot1(y=y1,p=4) [,1] [,2]

Hello, i wrote this function guete and now i want to plot it: but i get this error message. i hope someone can help me. Error in dim(robj) <- c(dX, dY) : dims [product 16] do not match the length of object [1] p_11=seq(0,0.3,0.1) p_12=seq(0.1,0.4,0.1) guete = function(p_11,p_12) { set.seed(1000) S_vek=matrix(0,nrow=N,ncol=1) for(i in 1:N) { X_0=rmultinom(q-1,size=1,prob=p_0)

I have been making some segment plots with five variables. They work great, especially when I used a different scale function, which scaled them by area of the circle rather than radius scale <- function(x, Mr = 1 , Mx = 100) { ((x/Mx)^.5)*Mr} Where x is the the value, Mr is the Maximum radius, and Mx is the maximum data value. You could change the exponent .5 to .57 if you wanted Flannery

hi i try to do a graph of a time series which shows in red the values > -0.05, in blue the values >0.05 and in white the values between -0.05 and 0.05 for un exemple :http://www.appinsys.com/globalwarming/enso.htm thanks !!!!! denisse -- View this message in context: http://r.789695.n4.nabble.com/how-to-do-a-graph-with-tree-different-colors-tp4635206.html Sent from the R help mailing

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Dear all, I need to generate numbers from multivariate normal with large dimensions (5,000,000). Below is my code and the error I got from R. Sigma in the code is the covariance matrix. Can anyone give some idea on how to take care of this error. Thank you. Hannah > m <- 5000000 > m1 <- 0.5*m > rho <- 0.5 > Sigma <- rho* matrix(1, m, m)+diag(1-rho, m)

Thank you for your guys reply for my previous question. But I got one more question about the boxplot. With the code in the R-help: boxplot(len ~ dose, data = ToothGrowth, boxwex = 0.25, at = 1:3 - 0.2, subset = supp == "VC", col = "yellow", main = "Guinea Pigs' Tooth Growth", xlab = "Vitamin C dose mg", ylab =

Dear R helpers: I have tried many times to find some way to read a list into R. But I faid. Here is an example: I have a file 'List.txt' which includes data as follows: [[1]] [1] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.0 0.0 0.0 [19] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 [[2]] [1] 0.0000000 0.5000000 0.0000000 0.0000000

Hi, I'm trying to redefine the contrasts for a linear model. With a 2 level factor, x, with levels A and B, a two level factor outputs A and B - A from an lm fit, say lm(y ~ x). I would like to set the contrasts so that the coefficients output are -0.5 (A + B) and B - A, but I can't get the sign correct for the first coefficient (Intercept). Here is a toy example, set.seed(12161952) y

Dear R-help, I have been trying really hard to generate the following vector given the data (x) and parameter (alpha) efficiently. Let y be the output list, the aim is to produce the the following vector(y) with at least half the time used by the loop example below. y[1] = alpha * x[1] y[2] = alpha^2 * x[1] + alpha * x[2] y[3] = alpha^3 * x[1] + alpha^2 * x[2] + alpha * x[3] ..... below are