search for: calcium

HI, I am using Windows XP and R version 2.9.2. I have a data frame written by R similar to the following: Lab_ID Analysis_Soil Results -4MAD -2.5MAD +2.5MAD +4MAD 55003 Calcium-2008-116 900 961 1121.5 1656.5 1817 55003 Calcium-2008-117 3321 2175 2380.5 3065.5 3271 55003 Calcium-2008-118 3342 3155 4019 6899 7763 55003 Calcium-2008-119 1664...

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...

...nd then plot them, without having to take the logs myself. This may not be possible. Hobie Perry St. Paul, MN Deepayan Sarkar wrote: On 5/23/08, hobie perry wrote: > > Good afternoon. > > The basic plot function can automatically generate log scales as follows: > > plot(calcium ~ soil_ph, log="y") > > Here is my basic model in xyplot... > > xyplot(calcium+magnesium ~ soil_ph|depth*region) > > I would like the calcium and magnesium values to be reported on a log scale. > I have tried manipulating "scales" and "yscale.co...

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 -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-....

...a function so that I can run multiple findInterval functions for many different water-quality analyses (and I have to do this for many dataset) but it seems to fall apart when incorporated into a function. Run straighforward, the findInterval function works as desired, e.g. below, creating the new CalciumFlag column with the appropriate flag for, in this case, levels of calcium in the water: WQdata$CalciumFlag <- with(WQdata, ifelse(analysis == "Calcium", (flags <- c("Y", 'Q', "", "A") [findInterval(WQdata$value, c(-Inf, 0.027, 0.1, 100, Inf))])...

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 river suspended sediments. T...

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? Many thanks Gav > version _ platform i386-pc-mingw32 arch x86 os...

...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 BC-0.5|1996-04-19|Arsenic|0.01 : 1 BC-0.5|1996-04-19|Calcium|76.56 : 1 BC-0.5|1996-04-19|Chloride|12 : 1 BC-0.5|1996-04-19|Magnesium|43.23 : 1 BC-0.5|1996-04-19|Sulfate|175 : 1 BC-0.5|1996-04-19|Total Dissolved Solids|460: 1 (Other) :14880 I wan...

...A, NA, NA, NA), BOD..5.day = c(NA, NA, NA, 3.3, NA, NA, 2.1, NA, NA, NA, NA, NA, NA, NA, NA, 3.4, NA, NA, 2.4, NA, NA, NA, NA, NA, NA, NA, NA), Cadmium = c(NA, NA, 0.00021, 5.3e-05, NA, NA, NA, 0.0036, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA ), Calcium = c(2.3, 1.9, 2.3, 2, 2.2, 2, 2.5, 2, 2.2, 2, 1.7, 1.8, 1.8, 2.2, 2.1, 3.4, 2.2, 2.2, 2.6, 2.4, 2.6, 2.5, 2.1, 2.4, 2.3, 2.5, 2.6), Carbonaceous.BOD..5.day = c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_...

...and with some of the methodologies used: clustering, classification, MCMC, counting processes, is a big plus. For more information please visit: http://www.biomedicale.univ-paris5.fr/physcerv/C_Pouzat/PostDoc1.html The second position starting in September to develop methods for the analysis of Calcium imaging data from neuronal preparation is also available. Familiarity with neurophysiology is not required. Familiarity with R and with maximum likelihood estimation of models based on non-linear ODEs and PDEs is a big plus. For more information please visit: https://www2.cnrs.fr/DRH/post-docs07...

...e 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. >From each of the replicates in each of the treatments I measured pH and nitrate, sulphate, dissolved organic carbon, calcium, magnesium, nickel, cobalt, aluminum, and copper concentrations. I tried performing an NMDS using the following tutorial http://strata.uga.edu/software/pdf/mdsTutorial.pdf. However, I did not take into account sites or treatments. All the data was used without making those distinctions. I would l...

...# mh0 hminf <- function(v) 1/(1+exp(v+70)/6); # taumh htaum <- function(v) 272+(1499/(1+exp(-(v+42.2)/8.73))); Kminf <- function(v) 1/(1+exp(-(v+14.2)/11.8)); Ktaum <- function(v) 7.2-(6.4/(1+exp(-(v+28.3)/19.2))); # Reversal potential of intracellular calcium concentration # Nernst Equation using extracellular concentration of Ca = 13mM # eca ECa <- function(Ca2) 12.2396*log(13000/(Ca2)); #ECa <- function(CaI) 12.2396*log(13000/(CaI)); #Sum of all the Ca # function(v) CaTminf(v) + CaSminf(v); CaI <- gCaT*CaTm^3*Ca...

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

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,

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