similar to: quantile() and boxplot.stats()

Hello, When I plot or look at the error rate vector for a random forest (rf$err.rate) it looks like a descending function except for a few first points of the vector with error rates values lower(sometimes much lower) than the general level of error rates for a forest with such number of trees when the error rates stop descending. Does it mean that there is a tree(s) (that is built the first in

Hi, I have a simple question about quartiles in R, especially how they are calculated using the boxplot. Quartiles (.25 and .75) in boxplot are different from the summary function and also don't match with the 9 types in the quantile function. See attachment for details. Can you give me the details on how the boxplot function does calculate these values? Cheers, Rene Brinkhuis

I have read and reread the boxplot and the boxplot stats page, and I still cannot understand how and what boxplot shows. I realize that this might be due to me not knowing enough statistics, but anyway... First, how does boxplot determine the size of the box? And is the line inside the box the mean or the median (or something completely different?) And how does it determine how long out the

Hi! My name is Martin and I have a problem concerning the boxplot function in R. I want my boxes to be limited by the 1st and 3rd quartile and NOT the 'hinges' values that are the default setting in R. Do anyone knows if there is any command that I could do to change this default setting? Sincerely Martin Olofsson

How are the lower/upper whiskers defined in the default version of boxplot {graphics}? I tried help(boxplot) and searching www.rseek.org, but I was unable to determine an absolute answer. I checked out the definition of boxplot according to Wikipedia (http://en.wikipedia.org/wiki/Box_plot), but it also had several approaches listed for how the whiskers could be determined, so I'm just

I've just started using R and am still a neophyte, but I found the following curious result. I'm using the current version of R (2.5.1 (2007-06-27) ). Why are the results for the third quartile different in the output from the summary and fivenum commands? For the following data set 457 514 530 530 538 560 687 745 745 778 786 790 792

In a Box and Whisker plot, I thought that when there are outliers both abov= e and below the whiskers, then the whiskers should both be the same length = (plus or minus 1.5 times the inter-quartile range). If you look at the plot for SilwoodWeather on p.155 of The R Book you will = see that for November (month =3D 11) the upper whisker is shorter than the = lower, while for other months with

Another naive stats question. I'm trying to better understand what boxplots are telling me. I think what I see is the median and the boundaries of the 1st and 3rd quartiles. The whiskers represent the range of the data unless there are points which are outside "range" (default: 1.5) times the distance from the median to that quartile. Is that right? I've read the

Hi List, Just wondering where the documentation exists for the statistics which makeup the bwplot. I'm guessing that if R is like similar products that the graph is constructed as The median is the filled circle. The box surrounding the filled circle depicts the 25th and 75th quartile. The range of values is given by the dotted lines (?whiskers?) outside of each box, and possible

For boxplot(), is it possible to pass in a parameter to change the default way that the 1st and 3rd quartiles are computed? (specifically, I'd like to use type 6 described in the quantile function). Also, what are the options for how outliers are computed, and how can one change them? Thank you [[alternative HTML version deleted]]

hi, i'm using /"boxplot()"/ to show some data: x <- c(0.99, 0.97, 0.91, 0.72, 1.00, 0.99, 1.02, 0.90, 0.91, 0.90, 1.02, 0.90, 1.35, 1.01, 0.92) boxplot(x) is it correct when i say: /"Boxes represent interquartile ranges (IQRs); bold horizontal lines, medians; whiskers, lowest and highest values still within 1.5 x IQR; open circles, outliers."? /thanks in advance

Is the following behaviour of the quantile function what one would expect? > a <- 1:100 > quantile(a,.6) 60% 60.4 Philippe -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the

All - I have an example data frame x l.c.1 43.38812035 085 47.55710661 085 47.55710661 085 51.99211429 085 51.99211429 095 54.78449958 095 54.78449958 095 56.70201864 095 56.70201864 105 59.66361903 105 61.69573564 105 61.69573564 105 63.77469479 115 64.83191994 115 64.83191994 115 66.98222118 115 66.98222118 125 66.98222118 125 66.98222118 125 66.98222118 125 and I'd like to get the 3rd

I am very new to R so forgive me if this seems basic but I have done extensive searching and failed to come up with the answer for myself. I am trying to label a boxplot I have created with the values for the median, upper and lower quartiles and max and min values. I have been unable to do this or find anything on the net to say how it might be done. Is this possible and if so how? Regards,

Hi I need some help getting results from multiple linear models into a dataframe. Let me explain the problem. I have a dataframe with ejection fraction results measured over a number of quartiles and grouped by base_study. My dataframe (800 different base_studies) looks like > afvtprelvefs basestudy quartile ef ef_std entropy CBP0908020 1 21.6 0.53 3.27

Why am I getting a wrong result for quartiles? here is my code: > cbiomass = c(910, 1058, 929, 1103, 1056, 1022, 1255, 1121, 1111, 1192, > 1074, 1415) > summary(cbiomass) > IQR(cbiomass) The result R gives me is: For the summary > Min. 1st Qu. Median Mean 3rd Qu. Max. 910 1048 1088 1104 1139 1415 For IQR > 91.25 ********* The true Q1 is 1039

Dear list, How can I add the mean and standard deviation to each of the boxplots using the example provided in the boxplot function? boxplot(len ~ dose, data = ToothGrowth, boxwex = 0.25, at = 1:3 - 0.2, subset = supp == "VC", col = "yellow", main = "Guinea Pigs' Tooth Growth", xlab = "Vitamin C dose mg",

Hi All, Is the definition and/or algorithm for the 'Hinges' (upper and lower) in Boxplot available somewhere online? I would like to know a little more than what is described in boxplot.stats. In particular I am trying to understand exactly how it differs from the default (Type 7) of the quantile function. Many thanks, Fredrik

PR #7690 points out that if the confidence intervals (+/-1.58 IQR/sqrt(n)) in a boxplot with notch=TRUE are larger than the hinges -- which is most likely to happen for small n and asymmetric distributions -- the resulting plot is ugly, e.g.: set.seed(1001) npts <- 5 X <- rnorm(2*npts,rep(3:4,each=npts),sd=1) f <- factor(rep(1:2,each=npts)) boxplot(X~f) boxplot(X~f,notch=TRUE) I can

Hi,everyone i need to calculate quartile values of a variable grouped by the other variable . same as in aggregate function(only median,mean or functions is possible-i think so) Could you please help me to achieve the same for other quartile values(5,10,25,75,90) as for median using aggregate. Thanks in advance. data : zip price 60000 567000 60001 478654 60004 485647 60001