similar to: how to do the concentration-time profiles in R?

Hi, Dear all, When I run xpose4() in R and select "2: Basic goodness of fit plots", I get an error like this " Selection: 2Error in print(basic.gof(.cur.db)) : error in evaluating the argument 'x' in selecting a method for function 'print': Error in xvardef(v, object) : object '.cur.db' not found Could you please tell me how to treat it? Thanks,

Hi, when I run the below code,there is an error occured. could you please tell me how to treat it? > pdf('covariate.pdf') > par(mfrow=c(1,1)) > pairs(data2[,c("ID","TYPE","AGE","GNDR","HT")], + panel=function(x,y) { points(x,y); lines(lowess(x,y))}) Error in `[.data.frame`(data2, , c("ID", "TYPE",

Dear All, I have a data sets as shown below A (Patient ID ), B and C are the Concentration of drug in blood on day 1 and day 4, D is the difference in conc. To do this in R I have written a code as follows, identified the number of patients who have more concentration on day 4 . Here I want to identify specifically the patient ID (is he patient 1 or 2 or 5 and 7), whose concentration is more. How

Hi,all, when I run the below code,there is an error occured. could you please tell me how to treat it? > pdf('covariate.pdf') > par(mfrow=c(1,1)) > pairs(data2[,c("ID","TYPE","AGE","GNDR","HT")], + panel=function(x,y) { points(x,y); lines(lowess(x,y))}) Error in `[.data.frame`(data2, , c("ID", "TYPE",

Respected Sir/Madam, I am a research scholar of Department of Statistics, University Of Calcutta. I had downloaded the latest version of "BRugs", and installed it in R 2.15.1 both in 32 and 64 bits with the help of openBUGS 3.2.2. My problem is that one of the programmes which requires the package "BRugs" is giving me an error given below:

Hello-- I have a data for small population who took 1 drug at 3 different doses. I have the actual drug concentrations as well as predicted concentrations by my model. This is what I'm looking for: - Time vs Concentration by ID (individual plots), with each subject occupying 1 plot -- there is to be 9 plots per page (3x3) - Observed drug concentration is made up of points, and predicted drug

Dear all, I'm trying reproduce an example of bioassays Yielding Concentration-Mortality Data particularly control - adjustment model from book Bioassay of Entomopathogenic Microbes and Nematodes chapter 7 with R. I used glm with family=binomial and link=probit, but I do not know how to implement parameter gamma (control mortality - mortality of the untreated control insect in this exaple)

Hi, I'm using the ineq package to calculate some concentration measures (Gini, Herfindal, ...) and I was wondering if there's around also a function to calculate standard error on these measures. If not, is anybody aware of where I can find a reference on this point? Thanks. -- ======================================================== Angelo Secchi PGP Key ID:EA280337

Hi, folks, ###### food=c('fruit','fruit','fruit','drink','drink','drink') type=c('apple','apple','orange','water','soda','soda') value=c(2,3,1,5,7,6) data=data.frame(food,type,value) share=c((2+3)/(2+3+1),5/6,1/6,5/(5+7+6),13/18,13/18)

Hi all, Can anyone please guide me how to draw a Concentration ellipsoid for a bivariate system with a bivariate normal dist. having a VCV matrix : Sigma <- matrix(c(1,2,2,5), 2, 2) I would like to draw in using GGPLOT. Your help will be highly appreciated. Thanks, -- View this message in context: http://www.nabble.com/Concentration-ellipsoid-tp25315705p25315705.html Sent from the R help

Hello, Using the data and code below I've been using R to compare output from two different solute transport codes, the red contours are from verified code while the blue contours come from some modified code I've been working on. The goal is for the contours to match, and although there is currently a slight discrepancy this would be expected. The plot shows a pulse of infiltrating

Hi, I''ve got trouble when describe infinite loop. code snippet: def start_loop while true data = self.server.handle_client if data self.manager.dispatch(data) end end end without the loop, it is easy to test the logic. but how can I describe it to tell the developer ( me :-) ) that there should be an infinite loop inside. thanks. Regards, Peng

Realized when I moved nouveau over to using the atomic DP MST VCPI helpers that I forgot to ensure that we clamp the BPC to 8 to make us less likely to run out of bandwidth on a topology when enabling multiple displays that support >8 BPC - something we want to do until we have support for dynamically selecting the bpc based on the topology's available bandwidth, since userspace isn't

Dear R Users, I am working for the United Nations to construct a complete life table from an abridged table. I want to use the code of Hydman Filter by Rob J Hydman but an error sentence always appears and it simply doesn't run-- source("C:/R/Jamie/HymanFilter.R") Error in .C("spline_coef", method = as.integer(method), n = nx, x = x, : C symbol

Hi, I want to make a plot similar to sm1 (attached). The code I tried is: dcols <- densCols(x,y) smoothScatter(x,y, col = dcols, pch=20,xlab="A",ylab="B") abline(h=0, col="red") But it turned out to be s1 (attached) with big dots. I was wondering if anything wrong with my code. Thanks,Zhengyu -------------- next part -------------- A non-text

This is the series I've been working on for a while now to get all of the atomic DRM drivers in the tree to use the atomic MST helpers, and to make the atomic MST helpers actually idempotent. Turns out it's a lot more difficult to do that without also fixing how port and branch device refcounting works so that it actually makes sense, since the current upstream implementation requires a

This is the series I've been working on for a while now to get all of the atomic DRM drivers in the tree to use the atomic MST helpers, and to make the atomic MST helpers actually idempotent. Turns out it's a lot more difficult to do that without also fixing how port and branch device refcounting works so that it actually makes sense, since the current upstream implementation requires a

Dear Rich, It depends how the data is generated. Although I am not an expert in ecology, I can explain it based on a biomedical example. Certain variables are generated geometrically (exponentially), e.g. MIC or Titer. MIC = Minimum Inhibitory Concentration for bacterial resistance Titer = dilution which still has an effect, e.g. serially diluting blood samples; Obviously, diluting the

This is the series I've been working on for a while now to get all of the atomic DRM drivers in the tree to use the atomic MST helpers, and to make the atomic MST helpers actually idempotent. Turns out it's a lot more difficult to do that without also fixing how port and branch device refcounting works so that it actually makes sense, since the current upstream implementation requires a

'make check' fails on d-p-q-r-tests: > ##-- non central Chi^2 : > xB <- c(2000,1e6,1e50,Inf) > for(df in c(0.1, 1, 10)) + for(ncp in c(0, 1, 10, 100)) stopifnot(pchisq(xB, df=df, ncp=ncp) == 1) Error: pchisq(xB, df = df, ncp = ncp) == 1 is not all TRUE Execution halted Here is some more testing: xB <- c(2000,1e6,1e50,Inf) for(df in c(0.1, 1, 10)) for(ncp in c(0, 1,