similar to: ppoints (PR#7538)

When I look at ppoints I see: ppoints<-function (x) { n <- length(x) if (n == 1) n <- x (1:n - 0.5)/n } However Venables & Ripley (2nd ed, p 165) say ppoints() should return (i-1/2)/n for n>=11; (i-3/8)/(n+1/4) for n<=10. The version below should work as described: ppoints<-function (x) { n <- length(x) if (n <= 10) (1:n - 0.375)/(n + 0.25) else (1:n - 0.5)/n

Full_Name: Tobias Verbeke Version: 2.1.0 OS: GNU/Linux Submission from: (NULL) (81.247.252.229) Would it be possible to use a non-ambiguous example of expressing a day according to the ISO 8601 international standard in the first sentence of the Note section of ?strptime, e.g. "2001-04-18" instead of "2001-02-03" ? Yours, Tobias

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

Hi, This is essentially a reposting of http://tolstoy.newcastle.edu.au/R/devel/05/11/3305.html which had no responses, and the behaviour reported there persists in r-devel as of yesterday. (1) sort() with non-null partial > x = rnorm(100000) > keep = as.integer(ppoints(10000) * 100000) > system.time(sort(x)) [1] 0.05 0.00 0.04 0.00 0.00 > system.time(sort(x, partial = keep)) [1]

Dear R community. I am using the identify() function to identify outliers in my dataset. This is the code I am using: #################################################################### # Function to allow identifying points in the QQ plot (by mouseclicking) qqInteractive <- function(..., IDENTIFY = TRUE) { qqplot(...) -> X abline(a=0,b=1) if(IDENTIFY) return(identify(X))

Hi, I am trying to write a function with the following codes and I would like it to return the values for "alpha beta para parab " seperately. Then I would like to use this funstion for "variable" with factor "a" and "b". But the result turns out to be a matrix with element like "Numeric,2" ... I guess they are just the values for

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),

>>>>> 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

Wherever I look up the following reference the name of the author is spelled Mauchly contrary to the naming of the R function. Mauchly, J.W., Significance test for sphericity of a normal $n$-variate distribution, Annals of mathematical statistics, 11(1940), p. 204-209. Is this a typo on the original article (which R Core has corrected) or is it a typo in the function name ? Best regards, Tobias

The abline function can be used to draw the regression line when one passes the lm object as an argument. However, if it's an intercept-only model, it appears to use the intercept as the slope of the abline: mod <- lm(dist ~ 1, data = cars) plot(dist ~ speed, data = cars) abline(reg = mod) # nothing appears This behaves as documented, but might catch someone. Would it be an improvement

There is a trivial typo in ?title. Please find a patch below. Kind regards, Tobias Index: /home/tobias/Documents/workspace/Rdevel_svn/src/library/graphics/man/title.Rd =================================================================== --- /home/tobias/Documents/workspace/Rdevel_svn/src/library/graphics/man/title.Rd (revision 45972) +++

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 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)

Hi, I want to create upper and lower 95% confidence intervals for a p-p plot of an empirical distribution with a theoretical gamma distribution. This is my code: x<-rgamma(100,shape=2, rate=1) # empirical data fitdistr(x,"gamma") # fit a gamma distribution dist<-pgamma(x,shape=1.9884256 ,rate=0.8765314 ) # fitted distribution, using the loglikelihood estimated parameters

Dear List, As a way to learn R, I am trying out some of the examples shown in the Reference Cards. I use the following to read a column of numbers from Excel: x <- read.delim("clipboard") My questions are: 1. Why is it that the first number is omitted from the selected data range? How do I tell R to pick up the first number as part of the entire selection? 2. The next thing I

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

I often need to work with large vectors whose distribution I want to summarize by Q-Q plots. Since the vectors are large, I use a subset of quantiles, e.g. quantile(x, probs = ppoints(1000)) Unfortunately, this seemed to be taking too long for large x (much longer than 'sort'). I initially thought maybe quantile was doing something sophisticated (which I don't really need with a

List: I have 2 related questions: (1) first I have x-y-z data, where x & y are the geographic locations of point values, z. I need to perform a normal score transform on the z-values and maintain their geographic location. So, how do I go from columns x-y-z to x-y-z-t (or x-y-t), where the t-values are the normal score transforms of the z-values? Can I use qnorm(ppoints(data)) to do

L.S. Since some time there is a new r-project.org site as announced here: https://stat.ethz.ch/pipermail/r-announce/2015/000581.html The logo has changed on the site, but I fail to find a vector graphics file. For the previous logo I used to go to https://svn.r-project.org/R-dev-web/trunk/Logo/ Is there anything similar for the new logo? Many thanks in advance. Kind regards, Tobias --

hi, I wrote a set of R functions for estimating what is the probability function that best fits a set of data. I wrote them based in this response: /http://tolstoy.newcastle.edu.au/R/help/03b/1714.html/ I extracted the relevant segment of the link above: //> PPCC <- function(shape, scale, x) { # only for weibull / + x <- sort(x) + pp <- ppoints(x) + cor( qweibull(pp, shape=shape,