search for: isotopic

Happy Friday fellow R users. I need some help - I am trying to make a graph using ggplot 2 of some lead isotope ratios. Normally, the isotope mass number appears as a superscript before the chemical symbol. However, I cannot figure out how to do this ggplot2's axis labels. The closest I have come is using "." In front of the numbers I am superscripting e.g: ggplot(....

I really like to use R for all my graphs, and as I work with stable isotopes I want to have a proper chemical notation in my plots I have looked at ?plotmath, but didn't find the answer and also searched the R website. ------------------------------------------------------------------------ -- plot(1:10,xlab=expression(^{14}*C)) # I want to have a superscript with nothing in front, but it

I collected eggs laid by Springtails everyday over 28 days after swich to isotopically enriched diet. The eggs were pooled at day 7, 14, and 28 (+ day 0 = initial value) and analyzed for isotopes. After the diet switch the isotopic values of the adults and eggs change towards those of the new diet. Here are the d13C values (y) of the eggs: x y 0 -22.2 0 -22.2 0 -22.2...

Dear R-List, I would like to write nicely the names of some isotopes on a plot. The code bellow works fine. plot(1:10,1:10) text(c(2,4,8),c(2,4,8),labels=c(expression(italic(phantom(0)^{78}*Ge)), expression(italic(phantom(0)^{137}*Cs)), expression(italic(phantom(0)^{129*m}*Te))), cex=3 ) But, since I have a lot of

Dear R-List, I would like to write nicely the names of some isotopes on a plot. The code bellow works fine. plot(1:10,1:10) text(c(2,4,8),c(2,4,8),labels=c(expression(italic(phantom(0)^{78}*Ge)), expression(italic(phantom(0)^{137}*Cs)), expression(italic(phantom(0)^{129*m}*Te))), cex=3 ) But, since I have a lot of

Dear R-helpers, i have the following situation: i have a bunch of y=b0 + b1*x from different studies, and want to estimate a "general" y=f(x). I only have the b0,b1's and R-squareds. Should i weigh the separate equations by their R-squared? thanks Remko ^'~,_,~'^'~,_,~'^'~,_,~'^'~,_,~'^'~,_,~'^'~,_,~' Remko Duursma, Ph.D. student

...erent scales. Is this possible? I have searched through all the documentation I could find on the R homepage without luck and I like R very much and would rather not resort to using something like SigmaPlot for this seemingly simple thing. E.g. plotting the concentration of Oxygen and it's isotopic composition in the same graph. Thanks, Henrik ---------------------------------------------------------------------------- -------- Henrik Andersson Netherlands Institute of Ecology - Centre for Estuarine and Marine Ecology P.O. Box 140 4400 AC Yerseke Phone: +31 113 577473 h.andersson@nioo.knaw....

Hi there, I am trying to run an MCMC on stable isotope data from certain organisms to determine their dietary habits in the package SIAR. I have prepared my data according to Inger, R., Jackson, A., Parnell, A., Bearhop, S. : SIAR V4 (Stable Isotope Analysis in R) an Ecologist's Guide (also better known as 'SIAR for dummies'), which is as follows: - consumer data table (columns

Hello all, I'm relatively new to "R" and programming in general - I had previously used MatLab, but decided to make the transition to R, as the computational times are much better! Anyway, I'm trying to use R to run a gamma distribution model to estimate mean transit times of water moving through a hydrological catchment. My input are 3 .txt format files as follow:

Hi, I am using the lda function from the MASS library. I would to find the decision boundaries of each class and subsequently plot them. I wonder if anybody can offer any help on this topic? Below I applied the lda function on a small dataset of mine. Any help will be much appreciated. > library(MASS) >

Dear R-List, I want to use the label function (from Hmisc library) to allow for the names of my isotopes. library(Hmisc) library(lattice) library(grid) num <- c("78","137","129m") nom <- c("Ge","Cs","Te") df <- data.frame(GE78=seq(nom),CS137=seq(nom),TE129m=seq(nom)) if I use this function to create the labels : lab <-

Help! model1 <- siarmcmcdirichletv4(data, source, tef, concdep=0, 500000, 50000) Error in matrix(1, ncol = (numsources + numiso) * numgroups, nrow = (siardata$iterations - : invalid 'ncol' value (too large or NA) In addition: Warning message: In Ops.ordered((numsources + numiso), numgroups) : '*' is not meaningful for ordered factors Previous message, but more problems:

Hi all, recently, i tried making a package with my own functions - which worked fine, until i reinstalled MikTex (in Win2000). Now i get the error message: * checking for working latex ... NO * using log directory 'C:/Rlibs/R4PG.Rcheck' * checking for file 'R4PG/DESCRIPTION' ... OK * checking if this is a source package ... OK ERROR Installation failed. But i set the path to

Hi all... I?m making a chart dealing with frequencies of isotopes of various elements. For instance, I'd like the following text to appear on a chart with the "35" and "37" as superscripts: Based upon: 35Cl: 75% 37Cl: 25% I am having problems properly parsing the superscript that preceeds the "Cl", since there is no character ahead of the superscript (I saw

I would like to plot 3 best-fit models in a single panel of a lattice plot, superimposed on 3 corresponding datasets in the same panel. My goal is to show the models as lines of 3 different colors, and the data as points whose colors correspond to the model colors. In essence, I have two levels of grouping: 1) model vs. data, and 2) model number. Since there is only one ?groups? variable, I

Hi, I have network data in the form of a couple of edgelists containing weights in the format "x,y,weight" whereby x represents row header and y represents column header. All edgelists are based on links among 634 nodes and I need to convert them into a 634*634 weighted matrix. I searched for online help using possible keywords I know, but I could not find a clue how to do this in

Hello, I'm using R code that includes a residual permutation that was written as a supplement to the paper: Turner et al. 2010. A general hypothesis-testing framework for stable isotopes ratios in ecological studies. Ecology 91:2227-2233. The supplemental code is available at: http://www.esapubs.org/archive/ecol/E091/157/suppl-1.htm When I execute the function, no warnings are given

Hello All... I gave a task to my students that involved using mclust to look for clusters in some bivariate data of isotopes vs various mining locations. They discovered something I didn?t expect; the data (called tur) is appended below. p <- qplot(x = dD, y = dCu65, data = tur, color = mine) print(p) # simple bivariate plot of the data; looks fine mod1 <- Mclust(tur[,2:3]) mod1$G mod2

hi list, i am making some diagnostic plots using plot.lme(), my lme model was fit with the option na.action='na.exclude'. On the following (or similar) commands: plot(flu.trees.42.w25.10.2, resid(., type="p") ~ fitted(.)|species, abline=0) R returns an error message: Error in getData.lme(object) : couldn't find function "naAct" It turns out that the function

Dear R-helpers, excuse me if this is not exclusively an R-related question. I have data from a nested design, both temporally and spatially, and the reponse variable of interest is left-censored. That is, only values > "some treshold" are available, otherwise "LOW" is reported. Are there ways of building a linear model with both fixed and random effects, when the