search for: smean

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, function(x) mean(head(...

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 dataset, wher...

...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 rather inefficient. Any hint to vectorize this would be appreciated. toy = data.frame(group = c(rep(1,10),rep(2,8)), diam = c(rnorm(10),rnorm(8))) nsel = c(6,4) smean <- c(0,0) for (i in 1:2) smean[i] <- mean(toy$diam[1:nsel[i]]) Thanks Pedro [[alternative HTML version deleted]]

...an as well. So far I've been using a for loop > for doing it but when it comes to a large data set is rather inefficient. > Any hint to vectorize this would be appreciated. > > toy = data.frame(group = c(rep(1,10),rep(2,8)), diam = > c(rnorm(10),rnorm(8))) > nsel = c(6,4) > smean <- c(0,0) > for (i in 1:2) smean[i] <- mean(toy$diam[1:nsel[i]]) > > Thanks > > Pedro > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https:/...

...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, plot=TRUE) { nt <- rep(0, time) nt[1] <- n for(n in 2:time) { nt[n] <- 0.5*rnorm(1, Fmean, Fsd)*rnorm(1, Smean, Ssd)*exp(1)^(-(f+s)*nt[n-1])*nt[n-1]} if(out==TRUE) {print(data.frame(nt))} if(plot==TRUE) {plot(1:time, nt, type='l', main='Simulatio...

...levels and the mean values for these levels are being plotted with CIs. I am trying to reduce the text size for the labels for this variable. The first function below does not attempt to set the text size for the y axes, and all works well. xx2 <- with(xx,summarize(q27a, llist(Scanf,bumo), smean.cl.boot, conf.int=.90)) Dotplot(Scanf ~ Cbind(q27a,Lower, Upper)| bumo, xlim=c(5,10),cex=.6, par.strip.text=list(cex=.8), xlab="",main="", data=xx2) Now, when I add to the above function, scales=(cex=.5), as I show in the function below, the graph reduces the size of the y l...

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 function, but I only get results for ONE of the two parameters. I cannot cope with optimizing the two para...

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"),

...panel.abline(h=4.0, col = "grey") # works fine panel.lines(-d$chosenValveSetting, col="orange") # in the wrong place } xYplot(I(AmountInTank) + I(-UserOutFlow+UserInFlow) + I(EnvirInFlow) ~ Time.Step, data=subset(h, Version=="Linear increase"), nx=F, method=smean.cl.boot, type='b',lty.bands=c(2,2), ylim=c(-20,20), panel=pfunc) What am I doing wrong? Hmisc 3.6.0, but older versions reacted similarly. Thanks for your help! [1] http://tolstoy.newcastle.edu.au/R/help/06/01/18860.html

Any help with this problem would be greatly appreciated: I need to produce a custom plot i haven't come across in R. Basically, I want to show means, 1st standard deviation and 5th and 95th percentiles visually, using something resembling a boxplot. Is it possible to completely customize a boxplot so that it shows means as the bar (instead of, not as well as medians), standard deviations at

I'm teaching a class and using R for the first time. We're talking about the bootstrap, and I've been trying to get R to replicate some simple bootstrap programs with no success. I'd like to be able to use the boot.ci function to produce confidence intervals (non-parametric) for some simple statistics, and this requires first creating a "boot" object. The boot

Hello to all users and wizards. I am regulary using 'boxplot' function or its analogue - 'bwplot' from the 'lattice' library. But they are, as far as I understand, totally flawed in functionality: they miss ability to select what they would draw 'in the middle' - median, mean. What the box means - standard error, 90% or something else. What the whiskers mean -