similar to: QQ International - How to troubleshoot an app that wont run?

I'm a newbie, sorry in advance :p I have been searching here and reading threads and can't seem to find an answer, hence this post. I saw a nice example of what I am trying to do so I'll copy that format and perhaps it will illustrate better than I can explain. I'm using Ubuntu Hardy, 64bit. My only goal currently is to install the redist, using winetricks is the proper method

I got QQ International (version 1.0) to work via WINE under Mepis 8.5. Using winetricks, I installed all of the missing DLL's, and QQ now starts up and runs fine. ... except for the fact that it always shows me as being "Away". Even if I manually set my status to "Online", it changes me back to "Away" after a second or two. This only happens under WINE. I log in

I installed QCharts on my wine app on Mandriva. Qcharts has run fine in the past when using Ubuntu. Qcharts installed but when attempting to execute the program, the wine glass begins going around in circles for about 30 seconds, Qcharts does not open and the wine glass disappears. Is this a permission problem with Mandriva or something else. Thanks.

Hello, I am having two data set original and predicted. I want to dind QQ-plot fot it. I tried in following manner : >qq(original~predicted) and error was : Error in qq.formula(o ~ p) : y must have exactly 2 levels There is an option "qtype" which dosent make any difference. What is the correct way for plotting QQ-plot or am I missing something. -- Amar Kumar Nandan

I have 20 variables: 5,9,6,1,5,9,7,4,5,6,3,2,4,8,9,6,1,8,4,8 How do I calculate the corresponding quantiles from a normal distribution with the same mean and variance as the sample? Also, how do I draw a QQ plot of the data? Thanks for any help! -- View this message in context: http://www.nabble.com/Quantiles-and-QQ-plots-tf4925742.html#a14097909 Sent from the R help mailing list archive at

Hi, i am working on a data set with EDA. That includes QQ-Plots of residuals vs expected normal distribution. What puzzles me is that the range of ordinate and abscissae is so different: while the theoretical quantiles range from [-2, 2] the sample quantiles on the ordinate do extent from [-20, 50]. Quite obviously some kind of transformation is done. Although i intensively RTFM i could not

Hi everyone, I'm a newbie to wine, and am working on QQ or any other messengers in wine. My environment is : ubuntu 10.04, installed wine 1.1.42, QQ2009. And during my debugging, I also check some source code from latest wine 1.2-rc4. Although QQ's level is "garbage", but fortunately it works almost fine under wine, including login, text chat, ..... But the video call can only

Hi all, I am trying to test wheater the distribution of my samples is normal with QQ plot. I have a values of water content in clays in around few hundred samples. Is the code : qqnorm(w) #w being water content qqline(w) sufficient? How do I know when I get the plots which distribution is normal and which is not? Thanks, m [[alternative HTML version

Hi, is there any similar function in R to S function qq.loglogistic, which produces a Q-Q plot? Thanks a lot Pete

Hi, I am trying to figure out how to get the correlation coefficient for a QQ plot (residual plot). So to be more precise, I am creating the plot like this: qq.plot(rstudent(regrname), main = rformula, col=1) But want to also access (or compute) the correlation coefficient for that plot. Thanks, Tom [[alternative HTML version deleted]]

Full_Name: Jarno Tuimala Version: 1.5.0 OS: Windows Nt Submission from: (NULL) (193.166.1.21) Running the following analysis gives as a result kukot vs. kisut. aikaero <- -27.5+5*(0:10) frekvenssi.m <- c(0,1,15,37,53,45,23,18,4,1,1) frekvenssi.n <- c(2,8,12,19,33,47,42,15,2,1,0) win.graph() aikaero <- rep(c(aikaero,aikaero), c(frekvenssi.m,frekvenssi.n)) a.ero <-

I'm new to R (and to S) and am wondering about code from pages 72 and 83 of MASS (Venables+Ripley, 3rd edition), to draw an envelope on a QQ plot. Copying from the book, I've got: #... code whose gist is "a.fit <- nls(..." num.points <- length(resid(a.fit)) qqnorm(residuals(a.fit)) # illustrate data-model residuals qqline(residuals(a.fit)) samp <-

I am attempting to use the R Commander Graphs Quantile-Comparison functionality on a dataset, to compare with a triangular distribution. I have the package triangle. My question is on the syntax of how to specify the parameters of the theoretical distribution in the Parameters field of the dialog box. For example, the theoretical distribution has min of 3000, max of 5000, mode of 4000. When

Hello everyone I'm a beginner in Stats and R, I'm using R 2.10.1. I need to create a multivariate qq plot, there is 8 variable group with each has 55 number of input. An example of what I did so far, just to get my point out: > data=read.csv(file.choose(),header=T) > data country village group av_expen P2ary_ed no_fisher 1 Cook Islands Aitutaki D

What's the current best wisdom on how to construct confidence bounds on something like a normal probability plot? I recall having read a suggestion to Monte Carlo something like 201 simulated lines with the same number of points, then sort the order statistics, and plot the 6th and 196th of these. [I use 201 not 200 because quantile(1:201, c(0.025, 0.975)) = 6 and 196 while

Dear R People: In the DASL library, there is a story about hot dogs. Here are the data: Beef 186 495 Beef 181 477 Beef 176 425 Beef 149 322 Beef 184 482 Beef 190 587 Beef 158 370 Beef 139 322 Beef 175 479 Beef 148 375 Beef 152 330 Beef 111 300 Beef 141 386 Beef 153 401 Beef 190 645 Beef 157 440 Beef 131 317 Beef 149 319 Beef 135 298 Beef 132 253 Meat 173 458 Meat 191 506 Meat 182 473 Meat 190

Hello! I am trying with this question again: I would like to test few distributional assumptions for some behavioral response data. There are few theories about true distribution of those data, like: normal, lognormal, gamma, ex-Gaussian (exponential-Gaussian), Wald (inverse Gaussian) etc. The best way would be via qq-plot, to show to students differences. First two are trivial: qqnorm(dat$X)

What does this mean? Code: Unhandled Exception: System.NullReferenceException: Object reference not set to an instance of an object. at System.Resources.ResourceManager.GetSatelliteAssembliesFromConfig() at System.Resources.ResourceManager.TryLookingForSatellite(CultureInfo lookForCulture) at System.Resources.ResourceManager.InternalGetResourceSet(CultureInfo culture, Boolean

Good Morning: I have attached a text file with one hundred thirty six observations. I would like to create a qq plot with the following features: 1. Observed values on the y-axis. 2. Normal approximation line on the plot. 3. X-axis with vertical reference lines at the following percentiles of the data: 1, 10, 20, 50, 80, 90 and 99. 4. Data appearing on the plot as distinct points. I assume that

Dear R helpers, I generate a qq plot using the following function call. qqmath(~val|ind,data=xx ,distribution=function(p) qt(p,df=19) ,ylab="Sample Quatinles" ,xlab="Theoretical Quantiles" ,aspect=1 ,prepanel = prepanel.qqmathline ,panel=function(x,y) { panel.qqmathline(y, distribution=function(p) qt(p,df=19),col=2)