similar to: AW: Looking for help in calculating percentiles

Dear List, I'd like to make boxplots of a large number of observations (+/- 20.000), which are distributed log-normal and right skewed. The problem is that with standard boxplots a too large number of observations are displayed as outliers. I also tried to display the log of the observations, but even then there are to may outliers to my taste. So I'd like to change the standard IQR box

The standard R boxplot appears to use quartiles to determine the height of the rectangles and a range parameter - RNG - (default=1.5 I think) that determines the length of the whiskers as <= RNG x Interquartile Range. Is it possible to instead define the range as extending to the 95th percentile? If so, how would this be done? nb, I'm plotting multiple boxplots on a single chart so a

Hi All: I am working with a dataset on Arsenic toxicity, and I am trying to calculate the 20th, 40th, 60th, 80th, and highest percentiles for a variable, dietary Moisture (variable name dMoist). The inbuilt function quantile(dMoist) would print 0, 25th, 50th, 75th, and 100th percentile. Does there exist a function that can calculate xth percentile (where x = 10th, 20th, ... etc) values?

Dear list, I am calculating the 95th percentile of a set of values with R and with SPSS In R: > normal200<-rnorm(200,0,1) > qnorm(0.95,mean=mean(normal200),sd=sd(normal200),lower.tail =TRUE) [1] 1.84191 In SPSS, if I use the same 200 values and select Analyze -> Descriptive Statistics -> Frequencies and under "Statistics", I type in '95' under Percentiles,

Type e.g.: quantile(x,0.1) or Quantile(x,0.8) Which calculates the 10th and 80th quantile Matthias Templ -----Urspr??ngliche Nachricht----- Von: arinbasu at softhome.net [mailto:arinbasu at softhome.net] Gesendet: Montag, 26. April 2004 09:29 An: r-help at stat.math.ethz.ch Betreff: [R] Looking for help in calculating percentiles Hi All: I am working with a dataset on Arsenic toxicity,

I was hoping to calculate the percentile for each date. So group all of one date together, calculating the value of the 2.5 and 97.5 percentile. -- View this message in context: http://r.789695.n4.nabble.com/Calculating-percentiles-for-multiple-dates-tp4638183p4638378.html Sent from the R help mailing list archive at Nabble.com.

Hi all, One quick question: How to put values of 25 and 75 percentile on boxplot? Thanks in advance. Nianqing Xiao, Ph.D NCI Center for Bioinformatics, NIH SAIC/Advanced Systems Group > 6116 EXECUTIVE BLVD 4026J > MSC 8335 > BETHESDA MD 20852 Phone: 301-451-6357 Fax: 301-480-4222 -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list --

Hi, I am using the package "demography" from Rob Hyndman for the Lee-Carter-Model. It is an amazing powerful tool but I am struggling with one issue: I want to compute different percentiles of the survival probability distribution derived from the Lee-Carter-Forecast (e.g. the 50%tile, 60%tile, 75%tile and 99%tile) for each of the next 10 years. Is there any possibility to retrieve

I have a 20x3 matrix as follows: > m <- replicate(3, matrix(rnorm(20),20,1)) I need to compute, say, 95th and 99th percentiles of each column such that the resulting matrix becomes 2x3 with each row representing the respective percentile. My "best effort" is to compute one column at a time as follows: > quantile(m[,1], c(0.95, 0.99)) To do the same for columns 2 and 3, I

Dear List, I have some discrete data and want to calculate the percentiles and the percentile ranks for each of the unique scores. I can calculate the percentiles with quantile(). I know that "ecdf" can be used to calculate the empirical cumulative distribution. However, I don't know how to exact the cumulative probabilities for each unique element. The requirement is similar

Dear R-list, I try to calculate the 10- and 90-Percentile from grouped data. Using 'lappy' it works fine but I have no success with 'gapply': df <- data.frame(test = runif(100)) df <- df[order(df[,1]),] z <- rep(1:10, each = 10) lapply(split(df, z), function(x) quantile(x, probs=c(10,90)/100)) library(nlme) gapply(as.data.frame(df), which=1, function(x)

There appear to be reports in the literature that transform continuous independent variablea by the use of splines, e.g., assume the dependent variable is hot dogs eaten per week (HD) and the independent variable is waistline (WL), a normal linear regression model would be: nonconfusing_regression <- lm(HD ~ WL) One might use a spline, confusion_inducing_regression_with_spline <- lm(HD

Hi all, I'm just getting started with R and I would appreciate some help. I'm having trouble creating a boxplot with whiskers at the 95th and 5th percentiles instead of at 1.5 * IQR. I have read the relevant documentation, and checked existing mails on this topic. I found a small modification that should work : https://stat.ethz.ch/pipermail/r-help/2001-November/016817.html and tried to

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

I have 2 datafiles 'target' and 'observed' as shown below (I will gladly email these 2 small files to whomever). X25. And X75. Indicate the value of 25th and 75th-percentile of the target ('what should be') and the observed ('what is'). The i.value is simply the month. > target X i.value X25. X75. 1 one.month 1 10.845225 17.87237 2

I have a dataset of about 10^6 rows, each consisting of a timestamp, several factors, a string, some integers, and some floats. I'd like to graph this data in various ways, including straightforward ones (how many events per week over the past year for each of 4 values of some factor), some less straightforward. I've managed to do this by brute force, but I'd like to learn how to do

Heeeelp Given this data x <- c(1,5,100,300,250,200,550,900,1000) > quantile(x) 0% 25% 50% 75% 100% 1 100 250 550 1000 When I run the quantile, I can only know the value of the nth percentile I want to know what's the percentile position of each items in the list Sample 1 = 100% on the list has 1 or more 5 = more than x% on the list has 5 or more 100 = more than x% on the

Hi all, I have a problem on how R calculates Percentiles : Suppose I have following data set: > data1 [1] -16648185 -14463457 -14449400 -13905309 -13443436 -13234755 -12956282 -11660896 [9] -10061040 -9805005 -9789583 -9754642 -9562164 -9391709 -9212182 -9151073 [17] -9092732 -9068214 -8978151 -8943912 -8761890 -8632106 -8541580 -8501249 [25] -8234466 -8219015

I have a problem where I need to calculate the corresponding cohort percentile ranks for each of several variables. Essentially, what I need is a function that will calculate the distribution-free percentiles from each variable's data vector, returning a corresponding vector of percentiles: e.g.: percentile.my.data<-/function/(my.data) I tried to make ecdf() perform this task but

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