search for: 0.350

I have a file: x y z 0.025 0.025 1.65775 0.025 0.050 1.62602 0.025 0.075 1.63683 0.025 0.100 1.91847 0.025 0.125 2.00913 0.025 0.150 1.82222 0.025 0.175 1.70901 0.025 0.200 1.39759 0.025 0.225 1.39089 0.025 0.250 1.04762 If I read the file like this: data<-read.table("file.dat") How do I access the vectors x,y,z that are inside the dataframe data? I studied Venables and

the following the the lower.tri matrix in a file named luxry.car and i want to read it in R as a lower.tri matrix.how can i do? i have try to use help.search("read"),but no result what i want. 1.000 0.591 1.000 0.356 0.350 1.000

Dear R users, I'm trying to do betareg on my dataset. Dependent variable is not normally distributed and is proportion (of condom use (0,1)). But I'm having problems: gyl<-betareg(cond ~ alcoh + drug, data=results) Error in optim(par = start, fn = loglikfun, gr = gradfun, method = method, : initial value in 'vmmin' is not finite Why is R returning me error in optim()? What

I have a simple linear model (fitted with lm()) with 2 independant variables : one categorical and one integer. When I run summary.lm() on this model, I get a standard linear regression summary (in which one categorical variable has to be converted into many indicator variables) which looks like : Estimate Std. Error t value Pr(>|t|) (Intercept) -3595.3 2767.1 -1.299

Since the fact that gfortran performance has improved over the major releases, I decided to benchmark the current releases on a MacPro with the Polyhedron 2005 benchmarks using -ffast-math -funroll-loops -msse3 -O3. The results are... gcc release gcc 4.2.4 gcc 4.3.3 gcc 4.4-pre gcc 4.3.3/ gcc 4.4-pre/

Hi, I'm reading part of a table from postgres, so I'm getting a data frame. how can I extract the numerica values so I can operate on them. > res <- dbGetResult(mydata) > str(res) `data.frame': 5 obs. of 8 variables: $ cyx.1: num 0.149 -0.278 0.114 0.060 0.109 $ cyx.2: num 0.158 -0.070 0.063 0.149 0.150 $ cyx.3: num 0.052 -0.350 0.114 0.126 0.238

I am using acf() to get the autocorrelations of a time series. It works but I want to then get the autocorrelations into a simple list of numbers. > x <- acf(price_changes, lag.max = 12,type = "correlation",plot = FALSE) > x Autocorrelations of series ‘price_changes’, by lag 0 1 2 3 4 5 6 7 8 9 10 11 12 1.000

Duncan Sands <baldrick <at> free.fr> writes: > > > I would be happy if you give me an insight into what could have caused the > > difference. > > No idea. Maybe you forgot to turn optimizations on when compiling? Otherwise > you are going to have to send in your programs along with an explanation of how > you compiled them exactly (exact sequence of

Hi. I'm analysing some fish biological traits with a gam in mgcv. After several tries, I got this model log(tle) = sexcolor + s(doy, bs = "cc", by = sexcolor) +log(tl) sexcolor is a factor with 4 levels doy is "day of year", which is modeled as a smoother tl is "total length of the fish" The summary of this models is (only parametric coefficientes): Parametric

Dear R community members, I think I am asking a very simple question, but I really looked up in the faqs and manuals and found nothing helpful. I am trying to plot a data frame with the following structure (this is just a small extract): glo conc odor line series X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 X13 1 0 AIR LN1 UP -0.488

Dear list, I am confused on how to explain the interaction term in the context of "treatment contrast". for example, I have an data frame as below: sub group val 1 a group1 3.685625 2 a group1 3.407445 3 a group1 4.040920 4 a group1 2.890875 5 b group1 3.853280 6 b group1 4.113585 7 b group1 3.043250 8 b group1 3.800920 9 c group1 5.394305 10 c

Dear all I need to compute percentage changes of my data, but unfortunately they contain both negative and zero values, and I am quite confused on how to proceed. Searching the internet I found that many people ran into similar issues, with no obvious solution available. The last couple of weeks I've been playing with all the data transformations that I could think of. Below I will expose on

Hi, I am getting a warning message when I am fitting a generalized linear mixed model (m1.2 below). CHOLMOD warning: matrix not positive definite Error in objective(.par, ...) : Cholmod error `matrix not positive definite' at file:../Supernodal/t_cholmod_super_numeric.c, line 614 Any idea? Thanks for your help, Reza > sessionInfo() R version 2.4.1 (2006-12-18) i386-pc-mingw32

We are two french students and we have a problem concerning an exercize. We don't know how to resolve it. It would be fantastic if someone can help us. Thanks. Description: This study examined how the metabolic cost of locomotion varied with speed, stride frequency and body mass. Cost was determined by measuring oxygen consumption (?vo2?), analyzing the oxygen content in air inhaled and

Hallo all, I have the following glm model: f1 <- as.formula(paste("factor(y.fondi)~", "flgsess + segmeta2 + udm + zona.geo + ultimo.prod.", "+flg.a2 + flg.d.na2 + flg.v2 + flg.cc2", " +(flg.a1 + flg.d.na1 + flg.v1 + flg.cc1)^2", " + flg.a2:flg.d.na2 + flg.a2:flg.v2 +

Sorry for the long letter! I have recently started using R. For the start I have tried to repeat examples from Milliken & Johnson "Analysis of Messy Data - Analysis of Covariance", but I can not replicate it in R. The example is chocolate chip experiment. Response variable vas time to dissolve chocolate chip in seconds (time), covariate was time to dissolve butterscotch chip

Dear list I would like to be able to group terms in a formula using a function that I will call tvar(), eg. the formula Y ~ 1 + tvar(x:A) + tvar(z) + u + tvar(B) + tvar(poly(v,3)) where x,u and v are numeric and A and B are factors - binary, say. As output, I want the model.matrix as if tvar had not been there at all. In addition, I would like to have information on the grouping, as a vector

Hi, I am using R to do a principal components analysis for a class which is generally using SPSS - so some of my question relates to SPSS output (and this might not be the right place). I have scoured the mailing list and the web but can't get a feel for this. It is annoying because they will be marking to the SPSS output. Basically I'm getting different values for the component

> I would be happy if you give me an insight into what could have caused the > difference. No idea. Maybe you forgot to turn optimizations on when compiling? Otherwise you are going to have to send in your programs along with an explanation of how you compiled them exactly (exact sequence of commands) both for gcc and LLVM. Ciao, Duncan.

Dear R-help, I'd like ask for your opinion on choosing the "right" strategy for a particular dataset. We conducted 24-hour electric field measurements on 90 subjects. They are grouped by job (2 categories) and location (3 categories). There are four exposure metrics assigned to each subject. An excerpt from the data: n job location M OA UE all 0 job1 dist_200 0.297 0.072 0.171