similar to: Difficulty implementing "scales" in a lattice plot

Here are several ways to get there, but your original loop is fine once it is corrected: > for (i in 1:2) smean[i] <- mean(toy$diam[toy$group==i][1:nsel[i]]) > smean [1] 0.271489 1.117015 Using sapply() to hide the loop: > smean <- sapply(1:2, function(x) mean((toy$diam[toy$group==x])[1:nsel[x]])) > smean [1] 0.271489 1.117015 Or use head() > smean <- sapply(1:2,

Hi Pedro, This may not be much of an improvement, but it was a challenge. selvec<-as.vector(matrix(c(nsel,unlist(by(toy$diam,toy$group,length))-nsel), ncol=2,byrow=TRUE)) TFvec<-rep(c(TRUE,FALSE),length.out=length(selvec)) toynsel<-rep(TFvec,selvec) by(toy[toynsel,]$diam,toy[toynsel,]$group,mean) Jim On 4/3/16, Pedro Mardones <mardones.p at gmail.com> wrote: > Dear all; >

Dear all; This must have a rather simple answer but haven't been able to figure it out: I have a data frame with say 2 groups (group 1 & 2). I want to select from group 1 say "n" rows and calculate the mean; then select "m" rows from group 2 and calculate the mean as well. So far I've been using a for loop for doing it but when it comes to a large data set is

Dear useRs, I wrote a function that simulates a stochastic model in discrete time. The problem is that the stochastic parameters should not be negative and sometimes they happen to be. How can I conditionate it to when it draws a negative number, it transforms into zero in that time step? Here is the function: stochastic_prost <- function(Fmean, Fsd, Smean, Ssd, f, s, n, time, out=FALSE,

I'm using R (2.4.1) and Hmisc (3.3-1), and I'd like to plot confidence intervals using xYplot and smean.cl.normal (or smean.cl.boot) from Hmisc. You can do that using the summarize() to produce a new data.frame and then plot with xYplot, or by specifying method=smean.cl.normal in the xYplot. Both produce very similar graphs in all trivial examples I've tried, but not in the attached

Dear all, i would like to plot each value from my datasets as segment with defined transparency However, I didnt find out how to set the transparency. definition by "col=" in par() or segments() doesnt seem to work any suggestions? Thanks in advance. Kind regards, Robert Pazur example code: xx2 <-read.table("http://www.scandinavia.sk/data/R/0_05.csv", sep=";",

[Please keep r-help in the cc: list] I don't quite know how to interpret the difference between specifying effort as an offset vs. as weights; I would have to spend more time thinking about it/working through it than I have available at the moment. I don't know that specifying effort as weights is *wrong*, but I don't know that it's right or what it is doing: if I were

Hello list, I have the following function which, as you can see, uses mean: meanratings <- round(apply(stack03[,c(102:121)],2,function(x) (tapply(x ,actcode, mean, na.rm=T))), digits=1) The above function yields the following output: q27a q27b q27c q27d q27e q27f q27g q27h q27i q27j q27k q27l q27m q27o q27p 1 7.8 8.1 7.7 7.9 7.9 NaN NaN 8.4 7.8 7.0 7.6 NaN NaN 7.1 6.0 2

Hello, I want to find the parameters mu and sigma that minimize the following function. It's important, that mu and sigma are strictly positive. ----------------- optimiere = function(fmean,smean,d,x,mu,sigma) { merk = c() for (i in 1:length(d)) merk=c(merk,1/(d[i]^2)*(d[i]-1/(fmean*(1-plnorm(x[i],mu,sigma))))^2) return(sum(merk)) } ----------------- To do that I'm using the nlm

Previously, I've posted queries about this, and thanks to postings and messages in response have recently had some success, to the extent that there is now a package called nlmrt on the R-forge project https://r-forge.r-project.org/R/?group_id=395 for solving nonlinear least squares problems that include small or zero residual problems via a Marquardt method using a call that mirrors the nls()

It's equivalent to __printf, so prefer __scanf. Signed-off-by: Joe Perches <joe at perches.com> --- include/linux/compiler-gcc.h | 3 ++- include/linux/kernel.h | 8 ++++---- include/xen/xenbus.h | 4 ++-- scripts/checkpatch.pl | 6 ++++++ 4 files changed, 14 insertions(+), 7 deletions(-) diff --git a/include/linux/compiler-gcc.h

It's equivalent to __printf, so prefer __scanf. Signed-off-by: Joe Perches <joe at perches.com> --- include/linux/compiler-gcc.h | 3 ++- include/linux/kernel.h | 8 ++++---- include/xen/xenbus.h | 4 ++-- scripts/checkpatch.pl | 6 ++++++ 4 files changed, 14 insertions(+), 7 deletions(-) diff --git a/include/linux/compiler-gcc.h

Hi All, I am trying to convert the following piece of matlab code to R: XX1 = sum(w(:,ones(1,N1)).*X1.*X1,1); #square the elements of X1, weight it and repeat this vector N1 times XX2 = sum(w(:,ones(1,N2)).*X2.*X2,1); #square the elements of X2, weigh and repeat this vector N2 times X1X2 = (w(:,ones(1,N1)).*X1)'*X2; #get the weighted 'covariance'

library(mvtnorm) # you were misusing "require"... only use require if you plan to library(ggplot2) # test the return value and fail gracefully when the package is missing set.seed( 1234 ) xx <- data.frame( rmvt( 100, df = c( 13, 13 ) ) ) xx2 <- expand.grid( X1 = seq( -5, 5, 0.1 ) # all combinations... could be used to fill a matrix , X2 = seq( -5, 5, 0.1 )

On some systems (alpha), tick marks don't appear on plots. The easiest way to see the problem is something like: > plot(0:1,axes=FALSE) > axis(1,1:2) The problem is in X11_Line(...) from .../src/unix/devX11.c, which is so short I've included the whole function below: static void X11_Line(double x1, double y1, double x2, double y2, int coords, DevDesc *dd) {

Can someone explain why I am getting the following error: in the r code below? Error in solve.default(diag(2) + ((1/currvar) * (XX1 %*% t(XX1)))) : system is computationally singular: reciprocal condition number = 0 In addition: There were 50 or more warnings (use warnings() to see the first 50) The R code is part of a bigger program. ##sample from full conditional

Hi there: I have this configuration: |-----[Server 2] | [Internet]--------[Router]----------[Switch]------------ [Server 1] | |-----[PC1] | |-----[PC2] | |-----[PC3] Server 1 has IP 216.251.XXX.XX1 Server 2 has IP 216.251.XXX.XX2 PC1 has IP 216.251.XXX.XX3 PC2 has IP 192.168.XXX.1 PC3 has IP 192.168.XXX.2 How do I configure shorewall in SERVER 2 to block to/from the Internet Port 22

It has long been known that the C specification of *scanf() leaves behavior undefined for things like int i; sscanf("9999999999999999", "%i", &i); C11 7.21.6.2 P12 "Matches an optionally signed integer, whose format is the same as expected for the subject sequence of the strtol function with the value 0 for the base argument." C11 7.21.6.2 P10 "If this

Hello, I am trying to print a crosttabulation of mean,sd,n for a continuous variable crossclassified by anoother/s grouping variables. I came up with: xtab2 <- function(x,g1,g2) { funy <- function(z) list(mean(z,na.rm=T),sd(z,na.rm=T),length(z)) aa <- by(x,list(g1,g2),funy) bb <- matrix(unlist(aa),nrow=3 ,dimnames=list(c("mean","sd","n"),

Dear all, I am stumped at what should be a painfully easy task: predicting from an lm object. A toy example would be this: XX <- matrix(runif(8),ncol=2) yy <- runif(4) model <- lm(yy~XX) XX.pred <- data.frame(matrix(runif(6),ncol=2)) colnames(XX.pred) <- c("XX1","XX2") predict(model,newdata=XX.pred) I would have expected the last line to give me the