similar to: visible code

Hello, I have installed R on my Apple Laptop. Next I wanted to install the package Rcmdr which requires the package tcltk. But then I get errors like: The downloaded packages are in /var/folders/0p/0pD8fDrwHouNDsQ+k8dGmU+++TI/-Tmp-//RtmpSp4q7p/ downloaded_packages Loading required package: tcltk Loading Tcl/Tk interface ... Error in dyn.load(file, DLLpath = DLLpath, ...) : unable to

Dear R-users, Version V2.0 of the package mice is now available on CRAN for Windows, Linux and Apple users. Multivariate Imputation by Chained Equations (MICE) is the name of software for imputing incomplete multivariate data by Fully Conditional Specifcation (FCS). MICE V1.0 appeared in the year 2000 as an S-PLUS library, and in 2001 as an R package. MICE V1.0 introduced predictor selection,

Dear R-users, Version V2.0 of the package mice is now available on CRAN for Windows, Linux and Apple users. Multivariate Imputation by Chained Equations (MICE) is the name of software for imputing incomplete multivariate data by Fully Conditional Specifcation (FCS). MICE V1.0 appeared in the year 2000 as an S-PLUS library, and in 2001 as an R package. MICE V1.0 introduced predictor selection,

Hi Folks, I don't often grumble, but this time I've found myself inconvenienced by a posting stored on R-help archives: https://stat.ethz.ch/pipermail/r-help/2009-September/211095.html This was Karin Groothuis-Oudshoorn & Stef van Buuren's message on 10 September about the new version of MICE. This has been sent by software which inserted no line-breaks. As a result, each

I am using -mice- for multiple imputation and would like to use the gelman diagnostic in -coda- to assess the convergence of my imputations. However, gelman.diag requires an mcmc list as input. van Buuren and Groothuis-Oudshoorn (2011) recommend running mice step-by-step to assess convergence (e.g. imp2 <- mice.mids(imp1, maxit = 3, print = FALSE) ) but this creates mids objects. How can I

I have a data frame with data similar to this: NameA GrpA NameB GrpB Dist A Alpha B Alpha 0.2 A Alpha C Beta 0.2 A Alpha D Beta 0.4 B Alpha C Beta 0.2 B Alpha D Beta 0.1 C Beta D Beta 0.3 Dist is a distance measure between two entities. The table displays all to all distances, but the

I have two vectors x and y, which I would like to plot against each other. I am also displaying other data in this plot. However, I have about 1 million points to plot, and just plotting them x againt y is not very informative. What I'd like to do is to do sort of a continuous box plot. My x values goes from -1 to 1 and my y values from 0 to 1, so I?d like to plot the median and quantiles,

o <- (structure(list(sand.silt = structure(list(statistic = structure(185, .Names = "W"), parameter = NULL, p.value = 0.0478835773838087, null.value = structure(0, .Names = "location shift"), alternative = "two.sided", method = "Wilcoxon rank sum test with continuity correction", data.name = ".column by site"), .Names =

I would like to put three figures next to each other in a figure. I have been reading the introduction to R, section 12 several times now, and I still can't make heads or tails out of it. Lets say that I have three dataframes a, b, c, and I want to plot a$V1, b$V1 and c$V1 in separate plots simply using plot(), how do I put them next to each other? I am sorry if this is a FAQ, but I cannot

Hello, I've posted a question about this subject yesterday, but since there was no R code to comment, no one did. I'm trying to have the print method for class 'htest' print some extra information common in some test, like the time series linearity related tests. Many of them have an 'order' parameter, representing a lag or embedding dimension, and it would be a nice

Dear list, I'd like to use multiple imputations to try and save a somewhat badly mangled dataset (lousy data collection, worse than lousy monitoring, you know that drill... especially when I am consulted for the first time about one year *after* data collection). My dataset has 231 observations of 53 variables, of which only a very few has no missing data. Most variables have 5-10% of

I am new to R, and I couldn't find the answers to my question in a faq. This could however be because I didn't know what to look for...:) I have three classes of data, data for bacteria, archaea and eukaryotes. I wish to display these in a histogram where all of the values are used to calculate each column. But, I want each column split in three, where the size of each coloured area

I am trying to create some graphs with R and it seems to be able to do what I need. However, I have so far not been able to find any sort of explanation of how the graphics system works. I am for instance trying to create a multiple figure, and I seem to have to call plot.new() before every new plot command, I have however not found any explanation of what this actually does. ?plot.new does give

Hello! First of all I must appologize if this has been raised previously, but search provided by Robert King at the University of Newcastle seems to be down these days. Additionally let me know if such a question should be sent to R-help. I did a contribution to function hwe.hardy in package 'gap' during the weekend. That functions performs Hardy-Weinberg equilibrium test using MCMC. The

I am trying to make horizontal violin plots. I have tried both vioplot and simple.violinplot, but both of them seem to not be willing to take the horizontal option. Is this correct, or am I just bungling it somehow? For instance, for vioplot (from the example shown, with the horizontal modification): > vioplot(bimodal,uniform,normal, horizontal=TRUE) Error in median(data) : need numeric data

I have managed to create a data frame like this: > tsus_same_mean[1:10,] PID Grp Dist PercAln PercId 1 12638 Acidobacteria 0.000000000 1.0000000 1.0000000 2 87 Actinobacteria 0.000000000 0.9700000 0.9700000 3 92 Actinobacteria 0.008902000 1.0000000 0.9910000 4 94 Actinobacteria 0.000000000 1.0000000 1.0000000 5 189 Actinobacteria 0.005876733

Hello, everyone, I don't quite understand the following message: > TTT <- t.test(1:10, y=c(7:20)) > class(TTT) [1] "htest" > TTT@p.value Error: Trying to get slot "p.value" from an object whose class ("htest") is not defined > TTT$p.value [1] 1.855282e-05 Why the message says the class of TTT is not defined while class(TTT) gets

Hi all, I just used power.t.test() in Version 1.9.0 beta (2004-03-31) today under FC1. The following is the output: > power.t.test(delta = .5, power = .95, type = "paired") $n [1] 53.94062 $delta [1] 0.5 $sd [1] 1 $sig.level [1] 0.05 $power [1] 0.95 $alternative [1] "two.sided" $note [1] "n is number of *pairs*, sd is std.dev. of *differences* within

I have read and reread the boxplot and the boxplot stats page, and I still cannot understand how and what boxplot shows. I realize that this might be due to me not knowing enough statistics, but anyway... First, how does boxplot determine the size of the box? And is the line inside the box the mean or the median (or something completely different?) And how does it determine how long out the

Hi! I have a dataset that looks like this: 0.0 14 0.0 3 0.9 12 0.73 15 0.78 2 1.0 15 0.3 2 0.32 8 ...and so on. I.e. a value between 0 and 1, and a number I would like to plot this in a histogram-like manner. I would like to have a set of bins, each 0.1 wide, and plot the sum of values in column 2 that falls within each bin. I.e, in this case I would like the first bin, 0.0, to have the