similar to: relative frequencies for hist()

I have a data set for different time intervals. The data has three comment lines before data for each time interval. For each time interval there are 500 data points. I want to change the dataset such that I have the following format: t1 t2 t3 ................ 0.00208 0.00417 0.00625 ................. a1 a2 a3 ...................

Would like to try my luck to see if I can catch your eyes. I was trying to do some contrasts within ANOVA. I searched the archive and found a clue posted by Steffen Katzner ( http://tolstoy.newcastle.edu.au/R/help/06/01/19385.html) I have three levels for a factor names "StdLot" and want to make three comparisons, 1 vs 2, 1 vs 3 and 2 vs 3. First,

Hi, R-listers, Failed, when I tried to merge df1 and df2 by "codetot" in df1 and "codetoto" in df2. I want to know the reason and how to merge them together. Data frames and codes I have used were listed as followed. Thanks a lot in advance. df1: popcode codetot p3need BCPy01-01 BCPy01-01-1 100.0000 BCPy01-01 BCPy01-01-2 100.0000 BCPy01-01 BCPy01-01-3 100.0000 BCPy01-02

Dear Mao Jianfeng, "r-help-owner" is not the place for help, but: r-help at r-project.org (CC-ed here) In any case, strsplit() does the job, i.e.: > unlist(strsplit("BCPy01-01", "-")) [1] "BCPy01" "01" You can work with the whole variable, like: splitpop <- strsplit(df1$popcode, "-") then access the first part with >

Dear R-help, This is an example in the {Hmisc} manual under rcorr.cens function: > set.seed(1) > x <- round(rnorm(200)) > y <- rnorm(200) > round(rcorr.cens(x, y, outx=F),4) C Index Dxy S.D. n missing uncensored Relevant Pairs Concordant Uncertain 0.4831 -0.0338 0.0462 200.0000

R gurus: I'm trying to get another round of rconifers out and I need some advice/help crushing differences in the examples test. I'm trying to make sure the max sdi values are being respected. I've added a tests/rconifers-Ex.Rout.save (from windows i386-pc-mingw32) and when I ran R CMD check (both R-2.13.0), I got the following results: * using log directory

Dear Rxperts, I have the following data: Study Study.Name C Category TC Time QC QO SD FSD Theta 1 NONE 0 P(22) 0 0.00 7.5596 0 0 8.0361e-03 0 1 NONE 6 G(50) 0 0.00 1.0000 0 0 0.0000e+00 0 1 NONE 2 F(02) 0 0.00 100.0000 0 0 0.0000e+00 0 1 NONE 3 F(03) 0 0.00 13.2280 0 0 1.6732e-02 0

Hi, all I wanted to fetch data from Bloomberg for govt bonds, and analyse it further. I am having trouble in getting data as when I use field=PX_LAST, it is giving the prices but when I use field=CPN, or ISSUE_DT, it is not giving the results and just bouncing back <NA> for that. This is the piece of code: > library(rJava) Warning message: package 'rJava' was built

Dear, When fitting the following model knots <- 5 lrm.NDWI <- lrm(m.arson ~ rcs(NDWI,knots) I obtain the following result: Logistic Regression Model lrm(formula = m.arson ~ rcs(NDWI, knots)) Frequencies of Responses 0 1 666 35 Obs Max Deriv Model L.R. d.f. P C Dxy Gamma Tau-a R2 Brier 701 5e-07 34.49

Dear All: I have the following data: 0 100 0.5 79.9605 0.75 84.7098 1.5 72.1793 2.5 97.4924 4.5 90.9696 8.5 59.9794 24.5 76.4859 456 100.0000 457.5 116.7381 460.5 118.7550 464.5

>> Doesn't work. Apparently the Dell UEFI PXE firmware doesn't know HTTP. > > There's a lot of variation. Do you have a shell option > in your boot selections? None of Dell OptiPlex 990 (firmware A19), 9010 (firmware A22), nor 9020 (firmware A16) seem have a built-in EFI shell option, but in all three cases I had success running the external EFI shell from

Hi All, This is not really an R question but a statistical one. If someone could either give me the brief explanation or point me to a reference that might help, I'd appreciate it. I want to estimate the mean of a log-normal distribution, given the (log scale normal) parameters mu and sigma squared (sigma2). I understood this should simply be: exp(mu + sigma2) ... but I the following code

Dear Experts, I am new to R and unfortunately cannot start with a simply statistical analysis: I manually determined the volume of the right and left hippocampus in a group of meditators and in a group of controls. My data-sheet looks as follows: observation subject group age gender hemisphere volume 1 am04 m 25 f left 3.637 2 am04 m 25 f right 3.713 3 ao08 m 47 m left 3.715 4 ao08 m 47

Hi all, This question is not really R related, rather on Statistics subject itself. Even I did not do those using R. however still I want to post it here, because my hope is I could get help from great statisticians who are the very active member of this group. My problem is to interpret Variance decomposition of VAR model in layman's language. Using EViews I got following : Variance

Hello, Apologies if this is the wrong list, I am a first-time poster here. I have an experiment in which an output is measured in response to 42 different categories. I am only interested which of the categories is significantly different from a reference category. Here is the summary of the results: summary(simple.fit) Call: lm(formula = as.numeric(as.vector(TNFa)) ~ Mutant.ID, data =

So I have a function that does lapply's for me based on dimension. Currently only works for length(pivotColumns)=2 because I haven't fixed the rbinds. I have two versions. One runs WAYYY faster than the other. And I'm not sure why. Fast Version: fedb.ddplyWrapper2Fast <- function(data, pivotColumns, listNameFunctions, ...){ lapplyFunctionRecurse <- function(cdata, level=1,

R gurus, I'm working on data analysis for a small project. My response variable is total vines per tree (median = 0, mean = 1.65, min = 0, max = 24). My predictors are two categorical variables (four sites and four species) and one continuous (tree diameter at breast height (DBH)). The main question I'm attempting to answer is whether or not the species identity of a tree has

Hi there! I´m a noob when it comes to R and I´m using it to run statisc analysis. With the code for ARIMA below I´m getting this error: Error in solve.default(res$hessian * n.used) :Lapack routine dgesv: system is exactly singular The code is: > s.ts <- ts(x[,7], start = 2004, fre=12) > get.best.arima <- function (x.ts, maxord=c(1,1,1,1,1,1)) + { + best.aic <- 1e8 + n <-

Dear All- I have a dataset that is comprised of the following: doy yr mon day hr hgt1 hgt2 hgt3 co21 co22 co23 sig1 sig2 sig3 dif flag 244.02083 2005 09 01 00 2.6 9.5 17.8 375.665 373.737 373.227 3.698 1.107 0.963 -0.509 PRE 244.0625 2005 09 01 01 2.6 9.5 17.8 393.66 384.773 379.466 15.336 11.033 5.76 -5.307 PRE 244.10417 2005 09 01 02 2.6 9.5 17.8 411.162 397.866 387.755 6.835 5.61 6.728

Hello, For numbers in the range 100 to 100,000,000 I'd like to decimal align a right-justified comma-delineated column of numbers, but I haven't been able to work out the proper format statement. format(num, justify=right, width=15, big.mark=",") gets me close, but numbers larger than 1,000,000 project a digit beyond the right edge of the column, which I really don't