similar to: documentation improvement request: add search (PR#12905)

Dear DevelopeRs, I've been struggling with the new regulations regarding modifications to the search path, regarding my Rcmdr plugin package RcmdrPlugin.DoE. John Fox made Rcmdr comply with the new policy by removing the environment RcmdrEnv from the search path. For the time being, he developed an option that allows users to put the environment from Rcmdr (RcmdrEnv) on the search path,

Luisfo, Thank you so much! That does what I need. Best regards, Tom On Mon, Apr 4, 2016 at 10:51 AM, Luisfo Chiroque <luisfo89 at yahoo.es> wrote: > Dear Thomas, > > Reading the probplot?s help page, it looks like it is using qqplot > underneath. > Thus, I think this is what you need. > probplot(x, line=FALSE) > #probplot(y, line=FALSE) > qq.y <- qqnorm(y,

Dear Thomas, Reading the probplot?s help page, it looks like it is using qqplot underneath. Thus, I think this is what you need. probplot(x, line=FALSE) #probplot(y, line=FALSE) qq.y <- qqnorm(y, plot=F) points(qq.y$y, qq.y$x) I hope this is useful for you. Best Regards, Luisfo Chiroque PhD Student IMDEA Networks Institute http://fourier.networks.imdea.org/people/~luis_nunez/

I think qqline does not do exactly what it is advertised to do ("`qqline' adds a line to a normal quantile-quantile plot which passes through the first and third quartiles."). Consider the graph: tmp <- qnorm(ppoints(10)) qqnorm(tmp) qqline(tmp) The line (which I expected go through all the points), has a slightly shallower slope than does the points plotted by qqnorm. I think

Do you know of a reference that discusses alternative choices for plotting positions for a normal probability plot? The documentation for qqnorm says it calls ppoints, which returns qnorm((1:m-a)/(m+1-2*a)) with "a" = ifelse(n<=10, 3/8, 1/2)? The help pages for qqnorm and ppoints just refer to Becker, Chambers and Wilks (1988) The New S Language (Wadsworth & Brooks/Cole),

Dear List, invoking qqnorm-plots in Version 63.3 produces funny things: using the option `type="s"´ on qqnorm should give a nice *line* of observed quantiles. Now, the line is walking along in order to the points index instead from lowest to highest, wich makes funny slopes. try x <- table(rnorm(1000) # or similar and qqnorm(x,type="s") # in 0.63.2 and 63.3 Well, the

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]]

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)

Stock returns and other financial data have often found to be heavy-tailed. Even Cauchy distributions (without even a first absolute moment) have been entertained as models. Your qq function subtracts numbers on the scale of a normal (0,1) distribution from the input data. When the input data are scaled so that they are insignificant compared to 1, say, then you get essentially the

Hello! I want to plot a P-P plot. So I've implemented this function: ppplot <- function(x,dist,...) { pdf <- get(paste("p",dist,sep=""),mode="function"); x <- sort(x); plot( pdf(x,...), ecdf(x)(x)); } I have two questions: 1. Is it right to draw as reference line the following: xx <- pdf(x,...); yy <- ecdf(x)(x); l <- lm(

Hello, I have a doubt about the plotting position of the theoretical quantile for the qqnorm command in R. Let F be the theoretical distribution of Y, we observed a sample of size n, y1,y2, ..., yn. We then sort it and comspare these empirical quantiles to the expected ones from F. For the plotting poition, there are several options: 1. i/(n+1) 2. (i-.375)/(n+.25) 3. (i- .3175)/ (n + .365) etc.

Dear All, I am a bit confused, I attached my data frame using 'attach(DATA)' Then I removed it using 'rm(DATA)' But for some reason it is still at position 2 at the search path search() [1] ".GlobalEnv" "DATA" "package:foreign" [4] "package:stats" "package:graphics" "package:grDevices" [7]

Hi I just would like to know, When I have a dataframe, like this one called 'dummy' And I attach it. Then I run my code. I then update the dataframe by making changes and I still call it 'dummy'. I run my code again. Now dummy is at position 1 and position 2 of the search path and if I run the code again, with another version of 'dummy' it updates and eventually my search

I request that the "freq" argument to hist be deprecated. Reason: One nice thing about SAS is is the consistency of certain inputs across many PROCs. In particular, they have "weight" and "freq" statements. We have added "weights" and "freq" to a number of functions in S-PLUS, listed below. I would like to see the same in R. In porting the

Hi all, I am a freshman of R,but I am interested in it! Those days,I am learning pages on NIST,with url http://www.itl.nist.gov/div898/handbook/eda/section3/probplot.htm, I am meeting a problem about probability plot and I don't know how to plot a data set with R. Could somebody tell me the answer,and a example is the best! I will look forward to your answer. Thank you very much.

>>>>> On Tue, 31 Aug 1999 14:57, Werner Stahel <stahel@stat.math.ethz.ch> said: WSt> Here is a suggestion. It seems that qqplots, comparing a sample WSt> to a distribution other than the normal, are not explicitly WSt> available in S or R. I found (in S-plus / Trellis it is, see below) WSt> qqplot(y, rt(300, df = 5)) WSt> as an

Hello all, I am using RSPerl package to display plots in R . I want to be able to compare some data in boxplot and in histogram and in probplot ( from e1071 package) - ( cumulative probability plot - normal) I have a nested arrray of data ... from perl like the following data[0][0] = (1,2,3,.....) data[0][1] = ( 2,1,2,2,2,2,2) - could be different lengths... etc ( could be more two sets to

Dear R People: I'm trying to build a package and am stuck on the last part; I keep getting "there is no library". Here are my statements: erin at erin-laptop:~/Desktop/R-2.9.1/bin$ R CMD check RcmdrPlugin.qual * checking for working pdflatex ... OK * using log directory '/home/erin/Desktop/R-2.9.1/bin/RcmdrPlugin.qual.Rcheck' * using R version 2.8.1 (2008-12-22) * using

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),

I recently updated all my plugins, and for the fun of it, I added ALL the Rcmdr Plugins to my collection to see what functionality might exist. I started Rcmdr and loaded ALL the available Plugins from to the Rcdmdr Tools menu. To my suprise Rcmdr produced a number of warnings and finally an error. The error suggests that some of the extensions are incompatable with each other because of menu