similar to: R summary

When all else fails, read the help page... ?fivenum says to look at ?boxplot.stats, and the "Details" section of ?boxplot.stats has, well, details. Tukey had reasons to call those hinges rather than quartiles. Andy > -----Original Message----- > From: Knut M. Wittkowski [mailto:kmw at rockefeller.edu] > Sent: Thursday, May 29, 2003 5:58 PM > To: Matthias Kirschner >

Dear R users, I've written the following functions to implement Silverman's modality test ("Using kernel density estimates to investigate multimodality", J.R. Stat. Soc. B, 43, (1981), 97-99.), and I tested them on the Chondrite data set (Good & Gaskins, J. Amer. Stat. Ass., 75, (1980), 42-56). Values for the critical window width seem OK, which is not the case for the

Hi, I'm trying to receive faxes using hylafax / iaxmodem but I just can't get it to work. We're using Sangoma E1 cards and have calls coming in over PSTN. I've tried turning hardware echo cancellation off but it makes no difference. This is what I get in /var/spool/hylafax/log: [root at faxhost log]# cat c000000003 Jan 14 12:44:43.39: [ 3403]: SESSION BEGIN 000000003 18005551212

Dear List, i am trying to produce a 3d plot using wireframe using the code: wireframe(Residuals_FD ~ Elevation * Temperature, data = data2, scales = list(arrows = FALSE), drape = TRUE, colorkey = TRUE) As you can see when the code (using the data below) is run the plot area is set-up correctly but the actual surface is missing? Any help would be greatly appreciated. Chris #data Elevation

Hi, a colleague ran a stepwise discriminant analysis twice in a row and got different results, suggesting some "sochasticity" in the algorithms involved. I looked at her data and found that there was a lot of collinearity, so that I reckoned that maybe "stepclass" (klaR) cannot find a clear winner when trying to include a new variable and makes a random choice. Is that true?

R Help - I'm trying to run a correlation matrix with a covariate of "age" and will at some point will also want to covary other variables concurrently. I'm using the "psych" package and have tried other methods such as writing a loop to extract semi-partial correlations, but it does not seem to be working. How can I accomplish this? library(psych) > set.cor(y =

I am using rw0641 with Windows 98. To list just the influential repetitiones that result from "influence.measures", I am using the input result <- lm(y~x) and the code from the example in the help for "influence.measures" INFLM <- function(result){ inflm <- influence.measures(result) which(apply(inflm$is.inf,1,any)) } It works fine up to now with the

Estimados Este es el test de friedman que se logra asi library(PMCMR) y <- matrix(c( 3.88, 5.64, 5.76, 4.25, 5.91, 4.33, 30.58, 30.14, 16.92, 23.19, 26.74, 10.91, 25.24, 33.52, 25.45, 18.85, 20.45, 26.67, 4.44, 7.94, 4.04, 4.4, 4.23, 4.36, 29.41, 30.72, 32.92, 28.23, 23.35, 12, 38.87, 33.12, 39.15, 28.06, 38.23, 26.65),nrow=6, ncol=6, dimnames=list(1:6,LETTERS[1:6])) print(y)

Hi all We are implementing samba-ldap to act as an nt pdc and are seeing performance problems. We have a 1ghz, 3gb Ram, 36gb box that is running samba-2.2.5 and openldap-2.0.23 under redhat 7.3 with kernel 2.4.18-3. Clients are all Win2k SP3. All the ldap requests are to the localhost interface. The box is acting as the PDC for the domain, and also sharing diskspace and printers. When we get

I apologize that I've asked a similar question before, but being new to R I don't think I did a very good job of formating the question. I've included a text file since the date set is somewhat large. What I have is a huge string of numbers in a text file. The numbers are all separated by comma's and the groups are separated by a semicolon. What I would like to do is read each

Hello R experts I have two linear regressions for sexes (Male, Female, Unknown). All have a good correlation between body length (response variable) and head length (explanatory variable). I know it is not recommended, but for a good practical reason (the purpose of study is to find a single conversion factor from head length to body length), the regressions need to go through the origin (0

I am stumped. I have a data set with multiple columns and about 65,000 case. Some of the cases have a "#NULL!" value so for dataframe "Props_": access_emp pct_vacant TAVAIL park PARKACRES totlandare 4538 52.15 #NULL! 0 1 22.99 74,129.70400 4539 52.15 .09 0 1 22.99 982,850.80400 10292 54.20

Hello R-help Below is the output from the predict() function. How can I assign $y to a variable. >predict(function,df2) $x        V1 1   36.28 2   34.73 3   33.74 4   69.87 5   58.88 6   89.44 7   43.97 8   41.94 9   33.34 10  38.47 11  35.16 12  42.94 13  46.76 14  53.24 15  52.43 16  50.40 17  34.42 18  33.22 19  33.24 20  39.60 21  39.32 22  44.71 23  54.03 24  47.48 25  35.42 26  34.78

Dear R, I'm trying to plot the first principle component of an analysis vs the first variable but am having trouble. I have no trouble doing the initial plot but have difficulty thereafter. First I want to highlight some points of the following data set list(running) [[1]] X100m X200m X400m X800m X1500m X5K X10K Marathon Argentina 10.39 20.81 46.84 1.81

Since the fact that gfortran performance has improved over the major releases, I decided to benchmark the current releases on a MacPro with the Polyhedron 2005 benchmarks using -ffast-math -funroll-loops -msse3 -O3. The results are... gcc release gcc 4.2.4 gcc 4.3.3 gcc 4.4-pre gcc 4.3.3/ gcc 4.4-pre/

At the cost of breaking the thread I'm going to change your subject and replace 'Principle' by 'Principal'. I just can't stand it any longer... OK, here is how I would solve your other problems. First put > wh <- c("USA", "New Zealand", "Dominican Republic", "Western Samoa", "Cook Islands") > ind

Dear Rusers, I have met a difficult problem on explaining the differences of principal component analysis(PCA) between R,S-PLUS and SAS/STATA/SPSS, which wasn't met before. Althought they have got the same eigenvalues, their coeffiecients were different. First, I list my results from R,S-PLUS and SAS/STATA/SPSS, and then show the original dataset, hoping sb. to try and explain it.

I have a data set p1982, its structure is the following Then I take 20 observations from this dataset, and assign to pr. in p1982, p has 1982 levels, in dataset pr, p should have 1 levels. But I do str(pr), it shows that p still has 1982 levels. also for these > pr$aa [1] ARG THR ASP CYS TYR ASN VAL ASN ARG ILE ASP THR THR ALA SER CYS LYS THR ALA LYS Levels: ALA ARG ASN ASP CYS GLN

This is a really simple question, I'm sure,but I can't make EpiR work! I keep getting the following: > epi.2by2(47, 263483, 282, 935028, method="cohort.time", conf.level=0.95) Error in epi.2by2(47, 263483, 282, 935028, method = "cohort.time", conf.level = 0.95) : unused argument(s) (935028) and I really don't know why!. Any ideas very very welcome thank

On 22 October 2013 16:21, Prakash Surya <surya1-i2BcT+NCU+M@public.gmane.org> wrote: > This probably belongs on the Lustre mailing list. I cross posted :) > Regardless, I don''t > think you want to do that (do you?). It''ll prevent any client side > caching, and more importantly, I don''t think it''s a case that''s been >