search for: 0.75

Hi, May be this helps: dat1<- read.table(text=" pbnr??????? dat? dep? dys? sop? ago? mis age female 1 10023 1994-02-21 0.75 1.00 0.50 0.50 0.75? 35????? 1 2 10023 1994-05-25 0.75 1.00 0.50 0.50 0.75? 35????? 1 3 10028 1994-02-01 2.00 1.75 3.00 0.50 1.50? 42????? 1 4 10028 1999-01-15 1.25 0.75 2.25 0.50 0.25? 42????? 1 5 10053 1994-03-16 2.50 0.75 1.25 0.50 1.25? 22????? 1 6 10053

I try to utilize some operations on rows in a matrix using command 'apply' but find a problem. First I write a simple function to normalize a vector (ignore error handling) as follows: normalize = function( v ) { return( ( v-min(v) ) / ( max(v) - min(v) ) ) } The function works fine for a vector: > normalize( 1:5 ) [1] 0.00 0.25 0.50 0.75 1.00 Then I generate a matrix: > a =

Hi, I'm trying to create a distance matrix. And it works out somewhat ok. However, I suspect that there are some efficiency issues with my efforts. Plz have a look at this: donor <- matrix(c(3,1,2,3,3,1,4,3,5,1,3,2), ncol=4) receiver <- matrix(c(1,4,3,2,4,3,1,5,1,3,2,1,4,5,3,5,1,3,2,4,5,1,2,3,1,4,5,5,1,2,1,3,4,3,2,5,5,1,4,2,5,4,3,2), ncol=4) The above creates my two matrices. I have

Hi all, I was trying to rebuild mtr (http://vault.centos.org/6.7/os/Source/SPackages/mtr-0.75-5.el6.src.rpm) and I keep getting: ==== Executing(%install): /bin/sh -e /var/tmp/rpm-tmp.gu9Ds0 + umask 022 + cd /root/rpmbuild/BUILD + '[' /root/rpmbuild/BUILDROOT/mtr-0.75-5.el6.x86_64 '!=' / ']' + rm -rf /root/rpmbuild/BUILDROOT/mtr-0.75-5.el6.x86_64 ++ dirname

Hi, i am new to this forum and not sure how it works, I am trying to do deskriptive descripe my data in terms of gender: head(scltotal) pbnr dat dep dys sop ago mis age female messpunkt2 messpunkt1 tage eintrittsjahr 1 10023 1994-02-21 0.75 1.00 0.50 0.50 0.75 35 1 8817 8817 0 1994 2 10023 1994-05-25 0.75 1.00 0.50 0.50 0.75 35 1 8910 8817

Hi, I'm stuck on creating a plot with x tick labels for every Nth tick mark - how is that done? I don't see a simple solution to this in help(plot) or help(par) and what I've tried is not working, eg, the following does not work, although it seems intuitive to me that it should work: x <- seq(-100,1000,25) y <- x * x % find all the x values that are multiples of 100 tmp <-

Hello, everyone, I have a question about integration of product of two densities. Here is the sample code; however the mean of first density is a function of another random variable, which is to be integrated. ## f=function(x) {dmvnorm(c(0.6, 0.8), mean=c(0.75, 0.75/x))*dnorm(x, mean=0.6, sd=0.15)} integrate(f, lower=-Inf, upper=Inf) ## error message Error in dmvnorm(c(0.6, 0.8), mean = c(0.75,

Folks, The contour() function wants x and y to be in increasing order. I have a situation where I have a grid in x and y, and associated z values, which looks like this: x y z [1,] 0.00 20 1.000 [2,] 0.00 30 1.000 [3,] 0.00 40 1.000 [4,] 0.00 50 1.000 [5,] 0.00 60 1.000 [6,] 0.00 70 1.000 [7,] 0.00 80 0.000 [8,] 0.00 90

Hi all, I've got a matrix of fractional data that is all positive and greater than zero that I would like to "loosely" classify, for lack of a better word. It looks something like this : 1.07 1.11 1.27 1.59 0.97 0.76 2.23 0.98 0.71 0.88 1.19 1.02 What I'm looking for is a way to round these numbers to the nearest 0.25, i.e. the above matrix would be

OK, so maybe last night was a little too much at one throw, so I have reduced the data to two stations- one that has precipitation and one that does not. This is going to be in the context of a larger data set. I would like to be able to issue a ggplot command and have cum sum just act on the facets (factors) to apply this. library(chron) library(ggplot2) DF <- structure(list(date_time =

Regardless of which version -- 1.1.1 or 1.2.0 (2000-11-27) -- with a fresh "directory" (i.e. no .RData), I am getting an extremely weird result. R : Copyright 2000, The R Development Core Team Version 1.2.0 Under development (unstable) (2000-11-27) > jj _ seq(0.05,0.95,by=0.002) > sum(jj==0.75) ## WRONG ANSWER [1] 0 > 0.05 + 350*.002 ## Double check that 0.75 is in jj [1]

Hello, I have R1.9.0 under Windows XP. My program plots several plots using x11() par(cex = 0.75) ...... x11() par(cex = 0.75) ...... x11() par(cex = 0.75) ...... x11() par(cex = 0.75) ...... Sometimes, one of them generates a small frame only with title area "R graphics: Device X (ACTIVE)". The message in the console window is Error in plot.new() : Figure margins too large

It built just fine in mock, results here http://li.nux.ro/download/nux/tmp/mtr6/ -- Sent from the Delta quadrant using Borg technology! Nux! www.nux.ro ----- Original Message ----- > From: "Digimer" <lists at alteeve.ca> > To: "CentOS mailing list" <centos at centos.org> > Sent: Tuesday, 8 March, 2016 00:05:59 > Subject: [CentOS] Can anyone compile

Folks, A few days ago, I had asked a question on this mailing list about making a contour plot where a function z(x,y) is evaluated on a grid of (x,y) points, and the data structure at hand is a simple table of (x,y,z) points. As usual, R has wonderful resources (and subtle complexity) in doing this, and the gurus of the list showed me the way. Here's a complete working example. One might

Dear all, I would like to ask one question related to statistics, for specifically on defining dummy variables. As of now, I have come across 3 different kind of dummy variables (assuming I am working with Seasonal dummy, and number of season is 4): > dummy1 <- diag(4) > for(i in 1:3) dummy1 <- rbind(dummy1, diag(4)) > dummy1 <- dummy1[,-4] > > dummy2 <- dummy1 >

Habría que buscar la vuelta, yo no lo se, pero posiblemente lo siguiente da una pista. Nota: al mismo código le sume una línea al final datos<-c(2,3,4,5,6,7,8) quantile(datos) quantile(datos,probs = c(0.25, 0.75, 0.85, 0.90, 0.95)) as.matrix(quantile(datos,probs = c(0.25, 0.75, 0.85, 0.90, 0.95))) as.data.frame(quantile(datos,probs = c(0.25, 0.75, 0.85, 0.90, 0.95))) # ¿ y si solo solicita

useR's, I am trying to find a quick way to change some values in a list that are subject to a condition to be NA. Consider the 3x1 matrix: delta <- matrix(c(2.5,2.5,1), nrow = 1) And consider the list named v that has 3 elements > v v[[1]] [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [1,] 4.25 3.25 2.25 1.25 0.25 0.75 1.75 2.75 3.75 4.25

useR's, Does anyone know of an efficient way to change the values in a list to different numbers stored in an object? For example, consider the following: y <- matrix(c(20, 13, 25, 10, 17), ncol = 1) > res [[1]] [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [1,] NA NA NA 1.25 0.25 0.75 NA NA NA NA NA NA 1.25 0.25 [2,]

Estimado Mauricio Monsalvo Le paso una idea, no es un código muy lindo que digamos, pero al correrlo seguramente se dará cuenta de mi sugerencia. datos<-c(2,3,4,5,6,7,8) quantile(datos) quantile(datos,probs = c(0.25, 0.75, 0.85, 0.90, 0.95)) as.matrix(quantile(datos,probs = c(0.25, 0.75, 0.85, 0.90, 0.95))) as.data.frame(quantile(datos,probs = c(0.25, 0.75, 0.85, 0.90, 0.95))) # ¿ y si solo

I have panel data in the following form: TIME X1 S1 1 1 0.99 1 2 0.50 1 3 0.01 2 3 0.99 2 1 0.99 2 2 0.25 3 3 0.75 3 2 0.50 3 1 0.25 ... ... ...... And desire a new vector of observations in which one column (S1 above) is sorted for each second from least to largest. That