similar to: Comparing Variables and Writing a New Column

I have a batch of data in each line of data contains three values, calcium score, age, and sex. I would like to predict calcium scores as a function of age and sex, i.e. calcium=f(age,sex). Unfortunately the calcium scorers have a very "ugly distribution". There are multiple zeros, and multiple values between 300 and 600. There are no values between zero and 300. Needless to say, the

Deepayan: Sorry for the additional email, but I'm concerned that I wasn't being clear. In the end, I would like a graphic that portrays my y-values on a log scale in their native data range. That is to say, I would prefer to see the axis labels as 1000 rather than 3 (log10 of 1000). Thank you for your kind assistance, Hobie Perry St. Paul, MN Hobie Perry <hobie_perry@yahoo.com>

Dear R Community, I hope you might be able to assist with a small problem creating a function. I am working with water-quality data sets that contain the concentration of many different elements in water samples. I need to assign quality-control flags to values that fall into various concentration ranges. Rather than a web of nested if statements, I am employing the findInterval function to

I am submitting the command: calcium<-read.table("calcium.txt",header=TRUE) and with Rw0630 and Bdr0631 I get an application error and R crashes. But the command works fine with rjune. I am running under NT4.0 Anyone have a similar problem? Jeff jmorris at ocdus.jnj.com -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

Dear Colleagues, I am attempting to develop an optimization routine for a river suspended sediment mixing model. I have Calcium and Magnesium concentrations (%) for sediments from 4 potential source areas (Topsoil, Channel Banks, Roads, Drains) and I want to work out, based on the suspended sediment calcium and magnesium concentrations, what are the optimal contributions from each source area to

Hi, I am trying to label the x-axis of some histograms with the units of measurement. However, when I use, for example: > truehist(Ca, prob=FALSE, col="gray", xlab=expression(paste("Calcium (", mu, eq^-1, ")"))) I get the following message: Error in eval(expr, envir, enclos) : Object "mu" not found Could someone let me know what I'm doing wrong?

I don't find how to do what I need to do in Dalgaard or 'R Cookbook', so I'm asking here. I have a data frame with water chemistry data and I want to start exploring these data. There are three factors (site, date, chemical) associated with each measurement. The data frame looks like this: > summary(chemdata) site_id.sample_date.param.quant

#is there a way to get NA in the table of descriptive statistics instead of the function stopping Thank you in advance #data x.f <- structure(list(Site = structure(c(9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L), .Label = c("BC", "HC", "RM119", "RM148", "RM179", "RM185",

Hi All I have been struggling with this model for some time now and I just can't get it to work correctly. The messages I get when running the code is: DLSODA- Warning..Internal T (=R1) and H (=R2) are such that in the machine, T + H = T on the next step (H = step size). Solver will continue anyway. In above message, R = [1] 0 0 DINTDY- T (=R1) illegal In above message, R = [1]

Two post-doctoral positions are available from the Brain Physiology Laboratory in Paris (France). The first position is available immediately to work on spike sorting and spike train analysis. It consists in both data analysis and methods development. Familiarity with neurophysiology is not required. Familiarity with R and with some of the methodologies used: clustering, classification,

Hello, I would like to perform an NMDS on the following: I have two independent variables, which are sites and treatments. I have 6 sites which are peatlands. I collected 5 replicates (at the same time) from each of the sites. I used each of the replicates in a treatment. There were 4 treatments. 2 were controls and the other two were a simulated 30 day drought and a simulated 60 day drought.

Hi All, I have a small dataset named das (43 cases) in which I am trying to create a binary outcome (1/0) based on the following code: if (das$age>65 && das$bmi>30) {das$danger<-1} else das$danger<-0 I am setting a flag called 'danger' to 1 of the subject is over 65 and has a BMI > 30. I find that my statement evaluates the first record in the data.frame and

Dear List As a fairly new R programmer I seem to have run into a strange problem - probably my inexperience with R After reading and merging successive files into a single data frame, I find that order does not sort the data as expected. I have multiple references in each file but each file refers to measurement data obtained at a different time. Here's the code library(reshape) #

I am so happy about learning how to read in multiple Excel files, that I have to try and make another improvement. I know what I have been doing is clumsy, but it works. Hopefully, someone can suggest a more elegant solution. As a novice, I have been using MS-Word and mail merge to write my code. I start with about 2 pages of code, and end up with 2,220 merged pages that I copy and paste into R.

I'm currently attempting to write a spec for parsing Markdown Extra, and since one goal is to minimize the differences in output between implementations, I've made a tool allowing me to compare who does what for any given input. I hope this can also facilitate future discussions about the syntax. So here's Babelmark, a testbed for various Markdown implementations were you

I''d like to delete some records before saving them. I ran this experiment: before_save :prune_lab_datas def prune_lab_datas lab_datas.each do |lab_data| lab_data.destroy end raise lab_datas.to_yaml end But nothing seems to be deleted in the hash: --- - &id001 !ruby/object:LabData attributes: created_at: 2010-03-21 22:16:06 unit_id: "3"

Dear R users, I have two data frames that were read from text files as follows: x_data <- read.table("x.txt", header = TRUE, sep = "|", quote = "\"'", dec = ".",as.is = TRUE,na.strings = "NA",colClasses = NA, nrows = 3864284, skip = 0, check.names = TRUE,fill=TRUE, strip.white = TRUE,

Hello All, I am a R newbie and am probably misinterpreting something really obvious... In the Rcmdr package there is a scatter3d() function that can fit a curve and also provide coefficients for the model. If I'm understanding this right, I think it's calling the lower level stats package function lm(), which is the part that actually does the curve fitting. Anyway, what has me

Dear R guru, I am Saikat Sarkar working as a researcher of Economics in Tampere University, Finland. I am trying to estimate some Garch related tests with Bayesian analysis by R programme. I am not good in R but trying to survive. Anyway I have the coding but not working properly. I have tried to find the problem but failed. I am writing to all R gurus to help me out. Could you please look at

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