similar to: help me

Hi, from what you're writing: "The logaritmic transformation "shapiro.test(log10(y))" says: W=0.9773, p-value= 2.512e-05." it seems the log-values are not distributed normally and so original data are not distributed like a log-normal: the p-value is extremally small! Other tests for normality are available in package: nortest compare the log-transformation of your ecdf

I am a beginner in R, so please don't step on me if this is too simple. I have two data sets datax and datay for which I created a qqplot qqplot(datax,datay) but now I want a line that indicates the perfect match so that I can see how much the plot diverts from the ideal. This ideal however is not normal, so I think qqnorm and qqline cannot be applied. Perhaps you can help? Ralf

Hi, We could use qqplot to see how two distributions are different from each other. To show better how they are different (departs from the straight line), how is it possible to plot the straight line that goes through them? I am looking for some thing like qqline for qqnorm. I thought of abline but how to determine the slope and intercept? Best wishes, Carol

For a financial data set with large variance, I'm trying to find the outlier threshold of one variable "x" over a two year period. I qqplot(x2001, x2002) and found a normal distribution. The latter part of the normal distribution did not look linear though. Is there a suitable method in R to find the outlier threshold of this variable from 2001 and 2002 in R?

Dear Community, I want to identify outliers in my data. I don't know how to use identify command in the plots obtained. I've gone through help files and use mahalanobis example for my purpose: NormalMultivarianteComparefunc <- function(x) { Sx <- cov(x) D2 <- mahalanobis(x, colMeans(x), Sx) plot(density(D2, bw=.5), main="Squared Mahalanobis distances, n=nrow(x),

My apologies in advance as this seem like an easy thing to fix. I am quite new to using R. I am doing my thesis at the moment and I am trying to use the extremes package. However, when I try to access it I get this message: The following object(s) are masked from ?package:stats?: > library( extRemes) Loading required package: tcltk Loading Tcl/Tk interface ... done Loading required package:

How do I generate a value in R from a poisson distribution with mean 20? Thanks! -- View this message in context: http://www.nabble.com/Generating-a-value-tf4922234.html#a14086120 Sent from the R help mailing list archive at Nabble.com.

I know this topic has had plenty of discussion in the last couple of days, but.... I've been trying to compare the effects of different fitted methods for systems of equations (OLS, SUR, 2SLS, 3SLS ) and would like to compare the residual plots (easy) and the qqnorm/qqplot of the fits for the different fitted methdos. For example, qqnorm( residuals( lm( q ~ p + f + a ) ) ) par( new = TRUE )

By any chance is any one aware of a website, book, paper, etc. or combinations of those sources that show plots of different distributions? After reading a pretty good whitepaper I became aware of the benefit of I the benefit of doing Q-Q plots and histograms to help assess a distribution.   The whitepaper is called: "Univariate Analysis and Normality Test Using SAS, Stata, and SPSS*" ,

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)

Hello, I'm Carla, an italian student, I'm looking for a package to transform non normal data to normality. I tried to use Box Cox, but it's not ok. There is a package to use Johnson families' transormation? Can you give me any suggestions to find free software as R that use this trasform? Thank yuo very much Carla ____________________________________________________________ 6X

Hy! I would like to know how run a montecarlo simulation with R. Thank you!!!! Francesca Matalucci __________________________________________________________________ Accesso Internet Gratis per utenti Excite! Attivalo subito! http://www.excite.it/hitech/accesso Il Mio Excite. Personalizza la tua Home page Excite come vuoi tu! http://www.excite.it AAA/Relazioni. Sfoglia gli annunci e trova la

I have written a function to emulate minitab's QQ plotting output (with SW test and AD test results on the graph): mtab.norm<-function(x) { library(nortest) library(lattice) x<-as.numeric(x) x<-as.vector(x) plot.ht<-4.6 plot.wd<-4.6 pt.ht=plot.ht/5 txt.sz<-(plot.ht/7.5) X11(width=plot.wd, height=plot.ht, bg='gray96') qqplot(x, pch=16, cex=pt.ht,

Hello, Our professor asked us to do probability plotting using weibull paper, exponential paper, normal, log-normal paper, etc. I know I can create Q-Q plot for normal dist. and see if all te points are on one line. How do I go about other distributions? I tried generating different samples and use the general qq function. However, I could not do it since I don't know the population

Hello, I once used the metawin software to perform a meta-analysis (see metawinsoft, Rosenberg et al.) and produced normal qqplot to test for a potential bias in the dataset. I now want to re-use the same dataset with the package metafor by W. Viechtbauer (great package btw). I run the qqnorm.rma.uni function. I use standardized effect sizes as in metawin. QQplot generated with metafor differs

Hello! I am using probplot in the e1071 package and want to do something like the following, only with the the 2nd plot overlaying the first. I can't seem to make it work. Any suggestions? *library(e1071) **x <- rnorm(100, mean=5)* *y <- rnorm(100, mean=3)* *probplot(x, line=FALSE) * *probplot(y, line=FALSE) * *Regards,* *Tom* [[alternative HTML version deleted]]

I've got a vector of data (hours to drive from a to b) y. After a qqplot I know, that they don't fit the normal probability. I would like to transform these data with the boxcox transformation (MASS), that they fit the model. When I try ybx<-boxcox(y~1,0) qqnorm(ybx) the plot is different from library (TeachingDemos) ybct<-bct(y,0) // qqnorm(ybct) How can I transform

Dear People, In a qqplot I am doing, I get lines/points that are very thick. I've tried setting the lwd variable to 0.1, but it doesn't seem to have any effect. Also, I have set the value of lty to dashed, but I still get dots. The command looks like qqplot(cdf.inv(seq(0,1,length=size),theta,pos,len),empmargdistvec(len,theta,pos,size), xlim=c(-theta,theta), ylim=c(-theta,theta),

Hi, When qqnorm on a vector of length 10M+ I get a huge pdf file which cannot be loaded by acroread or evince. Any suggestions? (apart from sampling the data). Thanks. -- Sam Steingold (http://sds.podval.org/) on Ubuntu 11.10 (oneiric) X 11.0.11004000 http://mideasttruth.com http://honestreporting.com http://camera.org http://openvotingconsortium.org http://pmw.org.il

Hi there, I'm a newbie, plesae bear with me. I have a dataset with about 10000 ~ 30000 data points. Would like fit to both Gamma and Normal distribution to see which one fits better. How do I do this in R? Or I could do a normality test of the data, if it's normal, I then will do a normal fit, otherwise, a gamma fit. But again, I don't know how to do this either. Please help! David