similar to: Sample mean in R

Dear All, I am running a simulation to obtain coverage probability of Wald type confidence intervals for my parameter d in a function of two parameters (mu,d). I am optimizing it using "optim" method "L-BFGS-B" to obtain MLE. As, I want to invert the Hessian matrix to get Standard errors of the two parameter estimates. However, my Hessian matrix at times becomes

Hi there, I am trying to write a function to perform GOF test of data to a zero-truncated Poisson distribution. I am facing 2 problems. 1) How can I obtain a frequency table for all values within the range of observed values? For instance if the observations are obs <- c("A", "A", "A", "A", "B", "C", "C", "D",

Here's one possibility, assuming muhat and sigmahat are estimtes of mu and sigma from N iid draws of N(mu, sigma^2): tStat <- abs(x - muhat) / sigmahat pValue <- pt(tStat, df=N, lower=TRUE) I'm not quite sure what df tStat should have (exercise for math stat), but given fairly large N, that should make little difference. Andy > From: Ross Clement > > Hi. I have a

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)

Hello, I have written a function that demonstrates the CLT by generating samples following the exponential distribution, calculating the means, plotting the histogram, and drawing the limiting normal curve as an overlay. I have the title of each histogram state the sample size and rate (1/theta) for the exponential (the output is actually 4 histograms), but I can't get the greek letter theta

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

Good evening dear administrators, It is with pleasure that I am writing to you to ask for help to finalize my R programming algorithm. Indeed, I attach this note to my code which deals with a case of independence test statistic . My request is to introduce the kernels using the functional data for this same code that I am sending you. So I list the lines for which we need to introduce the

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

Hm. Google tells me that kernel function is in stats package which comes with base installation and is invoked when you start R. search() [1] ".GlobalEnv" "package:stats" "package:graphics" [4] "package:grDevices" "package:utils" "package:datasets" [7] "package:methods" "Autoloads"

What do you *mean* "when you want to use the kernels". WHICH kernels? Use to do WHAT? In your browser, visit cran.r-project.org then select "Packages" from the list on the left. Then pick the alphabetic list. Now search for 'kernel'. You will find dozens of matches. On Wed, 14 Oct 2020 at 05:15, PIKAL Petr <petr.pikal at precheza.cz> wrote: > Hm. Google tells

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

Hello. Here is my R code. I used the functional data . Now I need to use the functional data by applying the kernels instead of the xi, yi functions. Bonjour. Voici mon code en R . J'ai utiliser les donn?es fonctionnelles . Maintenant j'ai besoin d'utiliser les donn?es fonctionnelles en appliquant les noyaux ? la place des fontions xi, yi library(MASS)

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