search for: 0.169

Dear R users I have a big matrix like 6021 1188 790 290 1174 1015 1990 6613 6288 100714 6021 1 0.658 0.688 0.474 0.262 0.163 0.137 0.32 0.252 0.206 1188 0.658 1 0.917 0.245 0.331 0.122 0.148 0.194 0.168 0.171 790 0.688 0.917 1 0.243 0.31 0.122 0.15 0.19 0.171 0.174 290 0.474

Full_Name: Adrian Custer Version: 0.90.0 OS: Linux on Thinkpad (pentium) and desktop (K6) Submission from: (NULL) (128.32.251.234) When I create a boxplot, and then try to overlay a lowess fit or just the points, the points do not appear in the highest level and the lowess curve does not reach the highest level. However, if I add one to each of the models, the problem is solved. I tried this

Hello, I am attempting to get the standard deviation in multiple distance bins in my spatial data. It appears as though the 'variog' command in the geoR package will do the trick, as one of the outputs from 'variog' is 'variog$sd', which, according to the manual, is the "standard deviation of the values in each bin". However, when I run this command, the

The file TENSILE.DAT from the Hand et al "Handbook of Small Data Sets" looks like this: 0.023 0.032 0.054 0.069 0.081 0.094 0.105 0.127 0.148 0.169 0.188 0.216 0.255 0.277 0.311 0.361 0.376 0.395 0.432 0.463 0.481 0.519 0.529 0.567 0.642 0.674 0.752 0.823 0.887 0.926 except that my mail client has replaced the tab separators by blanks. If I paste this data into R 2.2.1 what I get is

Hi r-users,   I would like to extract the data that match.  Attached is my data: I'm interested in matchind the value in column 'intg' with value in column 'rand_no' > cbind(z=z,intg=dd,rand_no = rr)             z  intg rand_no    [1,]  0.00 0.000   0.001    [2,]  0.01 0.000   0.002    [3,]  0.02 0.000   0.002    [4,]  0.03 0.000   0.003    [5,]  0.04 0.000   0.003    [6,] 

Hi, I try to build lldb with Cmake (gcc-5.3.0 is necessary for CUDA) on my "SUSE Linux Enterprise Server 12.2 (x86_64)". Unfortunately the build process breaks for lldb with the below mentioned error message. I've downloaded the following packages and configured with the following commands. svn co http://llvm.org/svn/llvm-project/llvm/trunk llvm cd llvm/tools svn co

I want to paste in the following numbers into a scan: 0.023 0.032 0.054 0.069 0.081 0.094 0.105 0.127 0.148 0.169 0.188 0.216 they are separated by tabs alone, unless my mailer has done something to the tabs. Now have a look at this: > scan() 1: 0.0230.0320.0540.0690.0810.094 1: 0.1050.1270.1480.1690.1880.216 Error in scan() : "scan" expected a real, got

Here is the file minimal.Snw: \documentclass[a4paper]{article} \title{R tips and tricks} \author{Murray Jorgensen} \usepackage{Sweave} \begin{document} \maketitle \section*{Entering data from a single variable} The following data are transformed tensile strength measurements on polyester fibres. They may be found on the file \texttt{TENSILE.DAT}. We may enter this data into R using the

Dear R members, I am new in using frailty models in survival analyses and am getting some contrasting results when I compare the Wald and likelihood ratio tests provided by the r output. I am testing the survivorship of different sunflower interspecific crosses using cytoplasm (Cyt), Pollen and the interaction Cyt*Pollen as fixed effects, and sub-block as a random effect. I stratified

I have a table like the following. I want to fit Cm to Vm like this: Cm ~ Cl+Q1*b1*38.67*exp(-b1*(Vm-Vp1)*0.03867)/(1+exp(-b1*(Vm-Vp1)*0.03867))^2+Q2*b2*38.67*exp(-b2*(Vm-Vp2)*0.03867)/(1+exp(-b2*(Vm-Vp2)*0.03867))^2 I use nls, with start=list(Q1=2e-3, b1=1, Vp1=-25, Q2=3e-3, b2=1, Vp2=200). But I always get 'singlular gradient' error like this. But in SigmaPlot I can get the result. How

Hi all, I am trying to run a glm with mixed effects. My response variable is number of seedlings emerging; my fixed effects are the tree species and distance from the tree (in two classes - near and far).; my random effect is the individual tree itself (here called Plot). The command I've used is: mod <- glmer(number ~ Species + distance + offset(area) + (1|Plot), family = poisson)

Dear R-helpers, I'm stuck with a little problem that surely has an easy solution but I can't think of a way to solve it. I'd really appreciate any help you can offer me! I'll provide a small example. Given a dataframe data.txt that looks like this: ID freq Var Var_mean Ratio_mean Var_median Ratio_median Var_sum Ratio_min Var_max Ratio_max Var_min

I'm trying to write a function to find the means over factors of the responses in a mlm (something I would do easily in SAS with PROC SUMMARY). The not-working stub of a function to do what I want is below, and my problem is that I don't know how to call aggregate (or some other function) in the context of terms in a linear model extracted from a lm/mlm object. means.mlm <-

I was reading about the project drawer feature in Textmate, which is Mac only. Is there a similar feature in a Windows based text editor that works with R. This feature sounds really useful. Thanks, Graham [[alternative HTML version deleted]]

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

Colleagues, I am analyzing data collected during oceanographic cruises. We have conducted many cruises over the last decade. On each cruise we visit ~50 stations. At each station (termed EventNum)we lower an instrument that measures depth, temperature, salinity and oxygen every few seconds as it is lowered through the water. Data from all EventNums on all cruises are stacked, generating a data

Hello all, I am working with a 1000x1000 matrix, and I would like to return a 1000x1000 matrix that tells me which value in the matrix is greater than a theshold value (1 or 0 indicator). i have tried mat2<-as.matrix(as.numeric(mat1>0.25)) but that returns a 1:100000 matrix. I have also tried for loops, but they are grossly inefficient. THanks for all your help in advance. Lanre

Hi everyone, I am having trouble with creating a loop to subtract arrays. In R, this is what I have done: > Vobsr <- read.csv("Observed_Flow.csv", header = TRUE, sep =",") # see data > below > Vsimr <- read.csv("1000Samples_Vsim.csv", header = TRUE, sep =",") # see > data below > Vobsr <- as.matrix(Vobsr[,-1]) # remove column 1 from

I suspect the weights argument is not having any effect. Package: Matrix Version: 0.995-2 Date: 2006-01-19 Beginning with this: Browse[1]> resp.lmer <- lmer(SensSSC ~ Block + Season + (1 | Plot) + (1 | Ma) + (1 | Pa) + + (1 | MaPa), weights = SensSSC.N, data = xx) I group the output into a table with my ran.eff function and get this:

Hello, I have some trouble using step() and stepAIC() functions. I'm predicting recruitment against several factors for different plant species using a negative binomial glm. Sometimes, summary(step(model)) or summary(stepAIC(model) does not select the best model (lowest AIC) but just stops before. For some species, step() works and stepAIC don't and in others, it's the opposite.