similar to: greek in main title

Dear R experts: Can you help me to overlap a histogram and theoretical density curve of poison distribution? for example data like this: The numbers of sanils found in each of 100 sampling quadrats in an area were as follows: number of snails, r 0 1 2 3 4 5 8 15 f=frequency of r 69 18 7 2 1 1 1 1 apparently this is not Poison but near to Poison, How to overlap the theoretical desity curve to

Hello, I was asked to try the following code on R, gamma.mles function (xx,shape0,rate0) { n<- length(xx) xbar<- mean(xx) logxbar<- mean(log(xx)) theta<-c(shape0,rate0) repeat { theta0<- theta shape<- theta0[1] rate<- theta0[2] S<- n*matrix(c(log(rate)-digamma(shape)+logxbar,shape/rate-xbar),ncol=1) I<- n*matrix(c(trigamma(shape),-1/rate,-1/rate,shape/rate^2),ncol=2)

Hi, there I'm trying to plot what is returned from a call to tapply, and can't figure out how to do it. My guess is that it has something to do with the inclusion of row names when you ask for the values you're interested in, but if anyone has any ideas on how to get it to work, that would be stellar. Here's some example code: y1<-rnorm(40, 2) x1<-rep(1:2, each=20)

Dear All I am totally new to R and I would like to know whether R is able and appropriate to illustrate to my students the Central Limit Theorem, using for instance 100 independent variables with uniform distribution and showing that their sum is a variable with an approximated normal distribution. Thanks in advance, Paul

I am having issues with the following: (muhat = 1/n^2(sum of all the xi's) ) essentially if xbar = the sample mean, muhat = sample mean but square the n. Question: Use R to run a Monte Carlo simulation which compares the finite-sample performance of xbar and muhat. Specifically generate 1000 samples n=30 from a standard normal distribution. For each sample calculate xbar and muhat. I have

I am new to R. I want to graph group data using a "Traditional Bar Chart with Standard Error Bar", like the kind shown here: http://samiam.colorado.edu/~mcclella/ftep/twoGroups/twoGroupGraphs.html Is there a simple way to do this? So far, I have only figured out how to plot the bars using barplot. testdata <- scan(, list(group=0,xbar=0,se=0)) 400 0.36038 0.02154 200 0.35927

Greets, My data looks like: > p3.18 s xbar subgroup 1 0.84 12.2 1 2 1.64 11.2 2 3 2.07 10.6 3 4 2.49 12.2 4 5 0.84 11.2 5 ... Using the command > qcc(p3.18$xbar,type="xbar",sizes=5,center=mean(p3.18$xbar),std.dev=mean(p3.18$s)/0.94,title="X-bar Chart for Paper Sheet Length Data") I get the x-bar chart I expect. However,

Dear Rusers, I would like to color different sections of a histogram different colors. I have an example that was done by "brute force" given below. Has anyone implemented something like this in general? If not, any suggestions/pointers on how to write a general function to do so would be most appreciated. Alan-

Dear all, I am a newbie in R and could not find help on this problem. I am trying to plot an histogram with probabilities in the y axis. This is the code I am using: #TLC uniform n=30 mi=1; mx=6 nrep=1000 xbar=rep(0,nrep) for (i in 1:nrep) {xbar[i]=mean(runif(n,min=mi,max=mx))} hist(xbar,prob=TRUE,breaks="Sturges",xlim=c(1,6),main=paste("n =",n), xlab="Média",

Hi Gents, I need to get the control limits from qcc function. As follows: qcc(MDI, type = "xbar.one") Call: qcc(data = MDI, type = "xbar.one") xbar.one chart for MDI Summary of group statistics: Min. 1st Qu. Median Mean 3rd Qu. Max. 0.3266 0.4249 0.4371 0.4333 0.4451 0.4858 Group sample size: 1 Number of groups: 383 Center

Hi Folks, I have data that looks like this: freq gender xBar 1000 m 2.32 1000 f 3.22 2000 m 4.32 2000 f 4.53 3000 m 3.21 3000 f 3.44 4000 m 4.11 4000 f 3.99 I want to plot two lines (with symbols) for the two groups "m" and "f". I have tried the following: plot(xBar[gender=="m"]~freq[gender=="f"]) followed by

Hi, I've had a quick look through the package list, and unless I've missed something, I can't seem to find anything that will do I-MR / Xbar-R / Xbar-S control charts ? Assuming there is something out there, can anyone point me in the right direction ? Thanks ! TIm

Hi, I wanted to understand exactly how acf and pacf works, so I tried to calculate ac and pac manually. For ac, I used the standard acf formula: acf(k) = sum(X(t)-Xbar)(X(t-k)-Xbar))/sum(X(t)-Xbar)^2. But for pac, I could not figure out how to calculate it by hand. I understand that in both R and EVIEWS, it is done using the Durbin-Levinson algorithm by the computer. However, I don't

Dear R users, I am stuck trying to figure out how to make a function return one value and print another.? Here is an example function: ################## eg <- function(x, digits=4) { xbar <- mean(x) sdx <- sd(x) value <- list(xbar, sdx) names(value) <- c("Mean of X", "SD of X") return(value)} ################## My current "solution" has been to

How do u calculated p values for a z test.. so far i ve done this A = read.table("cw3_data.txt") xbar = mean(A) s = 1 n = 20 mu = 0 z.test = (xbar-mu)/(s/sqrt(n)) p.value = pnorm(abs(z.test)) error = qnorm(0.99)*s/sqrt(n) left = xbar - error right = xbar + error and have got values off of it...but the values for p dont match up with other sites that i have used to check it

Dear Mac users, Hi, as you might have probably read the thread of "[R] Rsquared in summary(lm)" on May 10, it seems that Mac version of lm() seem to be working incorrectly. I enclose the script to produce the result both for lm() and manual calculation for a simple regression. Could you run the script and report with the version of R, so I don't have to go through every builds

Muchísimas gracias Carlos, de verdad que te agradezco la ayuda, pero no es lo que voy buscando. Quiero colocar en el eje de abscisas la secuencia temporal de los meses, es decir, agosto septiembre, octubre, etc? pero no las fechas de las toma de datos, sino que aparezca la marca de un mes, y la siguiente marca sea la del siguiente mes, etc?, y además que las muestras estén separadas de acuerdo con

Hello, I have no experience with I-MR charts but a google search found package qcc. Maybe it's what you're looking for. Hope this helps, Rui Barradas Em 08-07-2017 09:07, Tim Smith escreveu: > Hi, > > I've had a quick look through the package list, and unless I've missed > something, I can't seem to find anything that will do I-MR / Xbar-R / > Xbar-S control

For some reason, using the qcc package, I'm unable to use the plotmath notation in the title. Can anyone see what I'm doing wrong? library(qcc) a <- rnorm(100) qcc(a,type="xbar.one",title=expression(bar(X)),ylab=expression(CFU/ft^3) ) This seems to not let the expression be evaluated, so I tried:

Hello everyone, I want to calculate type I error rate for modified F statistic for one way robust anova. I need to find the j group trimmed mean and winsorized sum of squared deviations. Here I attached my code for j=2 to make it simple. Originally I have j=4. Hope you can help. I need to run it for 1000 times My problem is: i) the value of F-test obtain from my simulation below is in negative