similar to: how to get variance?

Hi all! I tried to perform Shapiro-Wilk test for my sample of 243 values. > Us [1] -10.4 -13.1 -12.2 38.1 -18.8 -13.3 -11.7 29.3 49.7 6.8 12.7 16.3 [13] 5.8 -0.7 -29.4 4.1 38.8 -1.4 8.8 15.6 32.9 -5.3 19.1 35.8 [25] 4.0 -1.5 0.6 -4.2 -10.0 -4.0 1.1 48.9 -21.0 -5.3 5.8 -10.8 [37] 21.9 8.2 -3.2 -3.9 -2.3 12.6 -4.7 -8.0 11.8 27.4 -9.5 -20.8 [49]

Could anyone help with what should be a simple task? I have data as a fixed format (fortran) table. I have no trouble getting it into R using read.table. Each column is separated by a space, including the first column that begins with a space, and aligned. It reads into R as if separated by tabs. However I want to manipulate two columns of data then write the results out into exactly the

I have a 45 x 16 data frame consisting of dissimilarities among 10 colors, giving in each column the 45 = 10*9/2 pairwise judgments for one of 16 subjects. The rownames identify each pair of colors, e.g, "AC" = ("A","C"), and the pairs are ordered by columns in the lower triangle of each distance matrix. > helm.raw <-

Dear R Users, I was hoping for some help with a recurrent error message in lmer. I am trying to model the effect of temperature on metabolic rate in animals (response = int.length) at different temperatures (mean.sst), with repeated measurements on the same individuals (random effect = female). Ideally I would make a random slope and intercept model where the rate can change differently with

Hello, It's an alternative to use SAS by function in R? I want to plot d histograms by plot.from example bellow: Thank you! plot d 1 1 16.3 2 1 25.0 3 1 57.8 4 1 17.0 5 2 10.8 13 2 96.4 17 3 76.0 18 3 32.0 19 3 11.0 20 3 11.0 24 3 106.0 25 3 12.5 21 4 19.3 22 4 12.0 26 4 15.0 27 5 99.3 32 7 11.0 36

Dear All I am quite new to R and would appreciate some help fitting 95% confidence intervals to a nls function. I have the data DOY CET 90 5.9 91 8 92 8.4 93 7.7 95 6.6 96 6.8 97 7.1 98 9.7 99 12.3 100 12.8 102 11 103 9.3 104 9.8 105 9.9 107 7.7 110 6.2 111 5.9 112 5.9 113 3.4 114 3.5 116 3.3 117 5.4 118 6.3 119 9.7 120 11.2 121 7.3 124 7.8 etc I am trying to use some code that has been

Dear all, I am attempting to explain patterns of arthropod family richness (count data) using a regression model. It seems to be able to do a pretty good job as an explanatory model (i.e. demonstrating relationships between dependent and independent variables), but it has systematic problems as a predictive model: It is biased high at low observed values of family richness and biased low at

my dataset looked like this in the beginning: >Daten V1 V2 V3 1 Dosis Gewicht Geschlecht 2 0 6.62 m 3 0 6.65 m 4 0 5.78 m 5 0 5.63 m I need box plots for V2 with all combination of V1 and V3, so I deleted the first row, and tried this: boxplot(Daten$V2[Daten$V3=="m"]) but it does not work and I

Dear Listserv, Here is my latest in a series of simple-seeming questions that dog me. Consider the following data: x <- read.table(textConnection("temperature probability 0.11 9.4 0 2.3 0.38 8.7 0.43 9.2 0.6 15.6 0.47 8.7 0.09 12.8 0.11 9.4 0.01 7.7 0.83 8 0.65 9.3 0.05 7.4 0.34 10.1 0.02 4.8 0.07 9.1 0.6 15.6 0.01 8.4 0.9 9.6 0.83 8 0.12 8.4 0.01 8 0 5 0.11 9.7 0.41 7.4 0.05 9.4 0.09

Hi there I thought this would be of particular interest to people using 'optim' functions and perhaps people involved with R development. I've been beaten down by R trying to get it to perform an optimization on a mass-balance model. I've written the same program in excel, and using the 'solver' function, it comes up with an answer for my variables (p, ACT, which

Good afternoon, I have a 63 small .csv files which I process daily, and until two weeks ago they processed just fine and only took a matter of moments and had non noticeable memory problem. Two weeks ago they have reached 318 lines and my script "broke". There are some missing-values in some of the files. I have tried hard many times over the last two weeks to create a

Hi, I'm having difficulty importing my textfile that looks something like this: #begin text file Timepoint 1 ObjectNumber Volume SurfaceArea 1 5.3 9.7 2 4.9 8.3 3 5.0 9.1 4 3.5 7.8 Timepoint 2 ObjectNumber Volume SurfaceArea 1 5.1

hi, I have a question about merging two files. For example, I have two files, the first file is like the following: id trait1 1 10.2 2 11.1 3 9.7 6 10.2 7 8.9 10 9.7 11 10.2 The second file is like the following: id trait2 1 9.8 2 10.8 4 7.8 5 9.8 6 10.1 12 10.2 13 10.1 now I want to merge the two files by the variable "id", I only want

First of all, sorry for the long mail. Inspired by the excellent analysis Rui did for lld, I decided to do the same for llvm. I'm personally very interested in build-time for LTO configuration, with particular attention to the time spent in the optimizer. Rafael did something similar back in March, so this can be considered as an update. This tries to include a more accurate high-level

I'm pretty sure that I did everything right, but my R is just not drawing the mosaicplot that I want, and there is also no error messege, looks like this right now: > mosaicplot(arthritis) > mosaicplot(~ sex + treatment + improved, data = arthritis, color = TRUE) > -- View this message in context: http://r.789695.n4.nabble.com/problems-with-mosaic-plot-tp3090128p3090128.html Sent

I want to make a stacked bar plot with one bar for two variables from my data "chir", the two variables have about 100 values like no, yes and na. I want to show how many no, yes and na they both have together with the stacked bar. I tried to melt these to variables first like this: melt1=melt(data_chir, measure.vars=c("N1_re", "N2_re"), var="zpd") but it

Hi, I've got a dataset with 7 variables for 8 different species. I'd like to test the null hypothesis of no difference among species for these variables. MANOVA seems like the appropriate test, but since I'm unsure of how well the data fit the assumptions of equal variance/covariance and multivariate normality, I want to use a permutation test. I've been through CRAN looking at

Hi all, I apologize for the ignorance implicit in this question, but I'm having a hard time figuring out how R functions work. For example, if I wanted to write a function to compute a variance, I would do something like >my.var <- function(x) (sum(((x-mean(x)))^2))/(length(((x-mean(x))) ^2)-1) And this seems to work, e.g., > my.var(V1) [1] 116.1 > var(V1) [1] 116.1

I've got a list of 5 matrices that are each 5 x 6. I'd like to end up with a 5 x 6 matrix that contains the mean value of the 5 original matrices. I can do this by brute force, but there must be a better way than making each matrix into a vector and then remaking a matrix thanks very much for any help david freedman ll=list(structure(c(9.7, 17.6, 20.8, 24.1, 33.8, 14.5, 25.7, 29.8,

dear R users, my data looks like this PM10 Ref UZ JZ WT RH FT WR 1 10.973195 4.338874 nein Winter Dienstag ja nein West 2 6.381684 2.250446 nein Sommer Sonntag nein ja Süd 3 62.586512 66.304869 ja Sommer Sonntag nein nein Ost 4 5.590101 8.526152 ja Sommer Donnerstag nein nein Nord 5 30.925054 16.073091 nein Winter Sonntag nein