search for: ppointed

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

Dear r-bugs, Whilst playing with ppoints I discovered that when one uses it directly, occasional NA's in a vector also become data fractions: ppoints(c(1,2,NA,4)) Would it be a good idea to add a warning message as in: ppoints <- function (n, a = ifelse(n <= 10, 3/8, 1/2)) { if(any(is.na(n))) warning("'n' contains NA's") if(length(n) > 1) n <-

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, 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,

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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),

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]

>>>>> 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

Hi all, I have managed to create a figure on the screen with multiple plots in it. Something like the example below. When I save that with ggsave(), only the last plot gets saved (pPath in the example) instead of the entire figure. Any suggestions how I can save this kind of figures automated? Thanks, Thierry library(ggplot2) pPoint <- qplot(unemploy/pop, psavert, data=economics) pPath

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, A very basic terrain calculated as a matrix from Spatial Points Patterns: #interpolate using the akima package library(akima) terrain=interp(ppoints$x,ppoints$y,ppoints$marks,xo=x0,yo=y0, linear=F) > class(terrain) [1] "list" > class(terrain$x) #these are the x-coord i.e: [1...1000] [1] "numeric" > class(terrain$y)#these are the y-coord i.e: [1...1000] [1]

Hi, does the shapiro wilk test in R-1.3.0 work correctly? Maybe it does, but can anybody tell me why the following sample doesn't give "W = 1" and "p-value = 1": R> x<-1:9/10;x [1] 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 R> shapiro.test(qnorm(x)) Shapiro-Wilk normality test data: qnorm(x) W = 0.9925, p-value = 0.9986 I can't imagine a sample being

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(

As a newbie to R, I'm still rather at a loss for finding information (the commands names can be rather arcane)so I'm just posting my question: I would like to estimate the shape coefficient of diverse distributions (Weibull, gamma and Tukey-Lambda specifically, but other could be of interest) - Does R have a PPCC utility to estimate such parameter?(maximum value of correlation coef)

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 all. I am seeking for a statistical suggestion. My data set comprises 382 measures each having 169 variables. Each measure is the outcome of a nuclear magnetic resonance experiment, so each of the 169 points has the same unit. As I want to do some multivariate calibration using these data, I checked whether some multivariate outliers existed. I calculated Mahalanobis distances and did a

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

Hi, Is there a function that does percentile-percentile plot. I do not mean the qqplot. I need to plot the percentiles rather than points themselves. I am hoping for a plot that tells me that the x percentile of one data set corresponds to the y percentile of the other. for example a point on the plot of (.5, .2) will tell me that the 50th percentile of the first data and the 20th percentile of