search for: logbeing

Hi all, I'm a PhD student at sydney uni and am trying to run a non linear mixed model program to obtain estimates of parameters describing dairy cow lactation curves. At present, I have been able to get the data to converge using the S plus (S plus 2000) nlme function. However, when I put the same data into R (R 1.9.0), add in the nlme package and run the code, it does not converge by the

Hi I'm sorry about the triviality of my problem. I have a vector (v) of three columns (logA, logB, id). I want to compute (and plot) the correlation between logA and logB for different thresholds of id (e.g. >30, etc). So I tried: for(i in 1:100){ points(cor(v$logA[v$id>i], v$logB[v$id>i], use="complete.obs"), i)) } (i created a plot object already) but it comes with

Dear all, Suppose I have a linear mixed-effects model (from the package nlme) with nested random effects (see below); how would I present the results from the random effects part in a publication? Specifically, I?d like to know: (1) What is the total variance of the random effects at each level? (2) How can I test the significance of the variance components? (3) Is there something like an

Hi all, given this example #start a<-c(0,70,50,100,70,650,1300,6900,1780,4930,1120,700,190,940, 760,100,300,36270,5610,249680,1760,4040,164890,17230,75140,1870,22380,5890,2430) length(a) b<-c(0,0,10,30,50,440,1000,140,70,90,60,60,20,90,180,30,90, 3220,490,20790,290,740,5350,940,3910,0,640,850,260) length(b) out<-ks.test(log10(a+1),log10(b+1)) # max distance D

Is there an R-language interface to the R API C-language functions Rf_logspace_add() and Rf_logspace_sub()? I don't see one but I may not looking under the right name. Various packages have functions which do that same sort of thing (log(exp(x)+exp(y)) and log(exp(x)-exp(y)) without unnecessary floating point errors). They have names like matrixStats::logSumExp(lx, na.rm=FALSE, ...)

...t; line in mongrel_cluster.yml to use production, ActiveRecord Sessions stop working. Changing this line to development yield the correct result. Entries in database.yml are correct, and confirmed that the sessions table exists in both environments and that production is indeed working (production.logbeing filled up). Any idea why this would happen ? Thanks Adam -------------- next part -------------- An HTML attachment was scrubbed... URL: http://rubyforge.org/pipermail/mongrel-users/attachments/20070423/10aa09de/attachment-0001.html

Dear R users, according the help(log), the function log2(x) should give the natural logarithm of x. I expect in case of x=2 to to get 0.6931, however, R gives me 1 as a result. Similar, logb(2,2) gives 1 again. I'm wondering if I have missed something ? Yours Frank -- Frank Mattes, MD e-mail: f.mattes at ucl.ac.uk Department of Virology fax 0044(0)207 8302854 Royal Free Hospital

Dear all, Suppose I have a linear mixed-effects model (from the package nlme) with nested random effects (see below); how would I present the results from the random effects part in a publication? Specifically, I?d like to know: (1) What is the total variance of the random effects at each level? (2) How can I test the significance of the variance components? (3) Is there something like an

Dear R-users, I am using R 2.13.0 and rms 3.3-0 , but can not reproduce figure 7.8 of the handouts *Regression Modeling Strategies* ( http://biostat.mc.vanderbilt.edu/wiki/pub/Main/RmS/course2.pdf) by the following code. Could any one help me figure out how to solve this? setwd('C:/Rharrell') require(rms) load('data/counties.sav') older <- counties$age6574 + counties$age75

Dear All, According to the Sturges rule, the number of classes of a histogram is the closest integer to 1 + logb(n,base=2) where n is the number of observations. The function hist(), by default, uses the Sturges rule. However, the code x <- 1:200 hist(x) produces a histogram with 10 classes and not 9 classes as determined by the Sturges rule. What am I missing? Thanks in advance, Paul

Survfit had a bug in some prior releases due to the use of both unique(times) and table(times); I fixed it by rounding to 15 digits per the manual page for as.character. Yes, I should ferret out all the usages instead, but this was fast and it cured the user's problem. The bug is back! A data set from a local colleage triggers it. I can send the rda file to anyone who wishes. The

Dear developers Neither Math.Rd nor Log.Rd mention the branch cuts that appear for complex arguments. I think it's important to include such information. Please find following two context diffs for Log.Rd and Math.Rd. [The pedants amongst us will observe that both sqrt() and log() have a branch point at complex infinity, which is not mentioned in the patch. Comments anyone?] rksh

Is there any way to know how the "dmvt" function computes the hypergeometric function needed in the calculation for the density of multivariate t distribution? -- View this message in context: http://r.789695.n4.nabble.com/hypergeometric-function-in-mvtnorm-tp4483730p4483730.html Sent from the R help mailing list archive at Nabble.com.

[ Not sure why, but the first time I sent this it never seemed to go through; apologies if you're seeing this twice ... ] I have some fully functional code that I'm guessing can be done better/quicker with some savvy R vector tricks; any help to make this run a bit faster would be greatly appreciated; I'm particularly stuck on how to calculate using "row-wise" vectors

What is wrong in the following nested if-else statements: if (Condition_1) { # begin IF_1 statement_1 statement_2 statement_3 if (Condition_2) { # begin IF_2 a<- a +1 } # end IF_2 statement_4 statement_5 statement_6 statement_7 if (Condition_3) {

I have a MLE task that for a small number of parameters finishes in a reasonable amount of time, but for my "real" case (with 17 parameters to be estimated) either takes far too long (over a day), or fails with "computationally singular" errors. So a) are there any parallel implementations of optim() (in R or otherwise) and b) how can I make my function more robust?

Dear R users, I don't know how to compute an exponential model like this: proc=a*exp(b*cls), or proc=a*exp(b*cls)+c*exp(d*cls). Please help me to solve this problem! Thank you! My data is: row.names proc cls 1 0.5 452.616206 0.5 2 1 255.864021 1.0 3 1.5 150.885316 1.5 4 2 86.289600 2.0 5 2.5 56.321559 2.5 6 3 39.504444 3.0 7 3.5 25.570308 3.5 8 4 5.382726 4.0 -- --- Catalin-Constantin

Maybe its slightly off-topic, but can anybody help with computing entropy on matrix of probabilities? Guess we have a matrix of probabilites, A, 2x2, something like this: z x 0 1 2 3 4 0 0.063 0.018 0.019 0.016 0.000 1 0.011 0.162 0.040 0.042 0.003 2 0.015 0.030 0.164 0.033 0.002 3 0.012 0.035 0.036 0.159 0.002 4 0.004 0.021 0.018 0.013 0.082 sum(A)=1 Can i

Hi, I would like to convert a decimal into a binary number, for instance : 2->(1,0) Any one knows how to do that ? Thanks a lot paul --- [[alternative HTML version deleted]]

x <- rnorm(1e6); y <- log(x); # or logb(x) or log1p(x) w <- warnings(); print(object.size(w)); ## [1] 480 str(w); $ NaNs produced: language log(x) - attr(*, "dots")= list() - attr(*, "class")= chr "warnings" y <- log2(x); # or log10(x) w <- warnings(); print(object.size(w)); ## [1] 8000536 str(w); ## List of 1 ## $ NaNs produced: language