similar to: QC add-on package

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

Hi all, I am using SPC techniques of plotting Xbar, R, S, P and C charts in R.For this I am using qcc package in R and also using the following document for reference. http://www.stat.unipg.it/~luca/Rnews_2004-1-pag11-17.pdf But while plotting S chart, R chartchart and also C chart I am getting following errors. I have plotted the Xbar chart successfully using following command obj <-

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

This regards an old post that posed the question: Tom Hodgess wrote: "The problem is the (apparent?) inability to produce moving range process behavior (a.k.a. "control") charts with individuals data in the package "qcc" (v. 2.0). I have also struggled with the same limitation in package "IQCC" (v. 1.0). The package "qAnalyst" (v. 0.6.0) provides an

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

I have been having the same problem as poster Hodgess, below. It appears that her question was never answered, so I would like to share a solution with the community. The problem is the (apparent?) inability to produce moving range process behavior (a.k.a. "control") charts with individuals data in the package "qcc" (v. 2.0). I have also struggled with the same limitation in

I''m just getting started with GD2 and have successfully made a few dynamic PNGs. I need to make some fairly detailed line graphs on the fly and I know that GD2 is capable of what I want but I strongly suspect I''m reinventing the wheel badly. Are there gems or other projects that help creating complex charts? I''ve used GDChart in the distant past but I

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,

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

Dear R-users, I'm encoutering some problems with the qcc()-function. When there are more than 25 replicates per "sample" the estimate for the standard deviation becomes NA, implying that nothing is plotted (error message: "Error in plot.window(...) : need finite 'ylim' values") On the forum I found a way to work around the error message, but this does not

Hi Ignacio, I'm running Centos 4.2 on some machines and just wonder which is the correct procedure to build one of your packages i've fonund in the fedora.ivazquez.net for FC4 but for CentOs for kernel-modules: http://fedora.ivazquez.net/yum/4/i386/SRPMS.ivazquez/kernel-module-qc-usb-0.6.3-0.iva.1.src.rpm

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)

hi. i was hoping to automatically set the Version: number in my package description file (image2k-package.Rd) in the man directory by using a .in file in the same directory. "R CMD build" excludes the .in file because the routine .check_package_subdirs() in QC.R (which build calls) doesn't like that file. .check_package_subdirs() also checks files in R/, and at *that* point in the

Dear R People: Is there a Quality Control in R book that would be accessible for undergraduates, please? I'm teaching a QC course in the fall semester and would be happy to have a Use R book or something like that, please. Thanks in advance, Erin -- Erin Hodgess Associate Professor Department of Computer and Mathematical Sciences University of Houston - Downtown mailto: erinm.hodgess at

Can someone make an rpm package for qc-usb-0.6.6.tar.gz on 2.6.18-308.el5.

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

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

Hi I am beginner with R I would like to compare the performance of Maximum likelihood Estimator (MLE) and Method of Moment Estimator (MME) effect probability of rejection, p. My MLE is x=rlnorm(10,meanlog = 2, sdlog =5) x xbar=mean(x) ssqrt=var(x) xbar ssqrt #MLE y=log(x) m1=mean(y) s1=var(y) m1 s1 #MME m2=log(xbar^2/sqrt(ssqrt+xbar^2)) s2 = log((ssqrt+xbar^2)/xbar^2) m2

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-

In one particular situation predict.coxph gives an error message. Namely: stratified data, predict='expected', new data, se=TRUE. I think I found the error but I'll leave that to you to decide. Thanks, Chris ######## CODE library(survival) set.seed(20121221) nn <- 10 # sample size in each group lambda0 <- 0.1 # event rate in group 0 lambda1 <- 0.2 # event rate in group 1