similar to: Extracting the dimnames of an array with variable dimensions

Dear All, I have some code that works in S-Plus for writing saving a graphics file to disk :- graphsheet(type = "auto", format = "WMF", file = "G:\\north0l.wmf", pages = "auto", print.background = F, orientation="landscape", color.style="color") plot(x,y) dev.off() This works fine in S-Plus. I have tried playing

Dear friends - I have a data.frame with "," instead of "." and found the discussion http://r.789695.n4.nabble.com/How-to-replace-all-commas-with-semicolon-in-a-string-tt4721187.html#a4721192 so copying the code of Ulrik(I hope:-)) I tried (making some data) AX <-

Dear R users I am using GLMMpql to analyse some nested negative binomial response data. How do I summarise the significance of my main effects? For example, in a standard linear mixed model (lme), I would use anova.lme to obtain an F statistic and P value for each of my main effects: how do I achieve a similar goal using GLMMpql? many thanks Sarah Richardson Sarah Richardson Plant

Dear members, Is there a way to turn a strwidth of a string into a number of lines that ist needed to display the string when using par(mar = c(?,4,4,2)) #### x = 1:5 names(x) = c("ZZZZZ","ZZZZZzzzzz","ZZZlllll","TTTTT","Zzhtsddfg" ) par(mfrow = c(1,2)) par(mar = c(8,4,4,2)) barplot(x, las = 3, main = "8 is to much") par(mar =

Hi all The code of trying to write relates to selecting properties (given by x and y co-ordinates) spatially (distance "X" from "infected" properties identified by date) over a certain time period. i.e. what properties are within 3 km from properties infected on "2008-01-01" over the last 14 days. Is any one able to give me some clues on how to write code to solve

I all I am just trying to get the idea of a loop if statement for another purpose. I was going to label a new variable based on date ie first week 1, second week 2 etc. My code in bold is wrong but seems logical to me, could someone help. x <- rep(c(2660156,2663703,2658165,2659303,2661531,2660914),c(2,2,2,2,1,1)) y <- rep(c(6476767,6475013,6475487,6479659,6477004,6476388),c(2,2,2,2,1,1))

Dear all, I an running R on a Windows 2000 machine (1.5Gb RAM) and am trying to load the lme4 package, however, whenever I attempt to load the library "lme4" I get the following error message I have installed lme4 and Matrix locally from the zip file with no problems. R version 2.6.2 (2008-02-08) Copyright (C) 2008 The R Foundation for Statistical Computing ISBN 3-900051-07-0

Hello R-helpers, A fundamental question ...I'm trying to understand the differences between loop and vectorization ... I understand that it should be a natural choice to use apply / adply when it is needed to perform the same function across all rows of a data frame. Any pointers on why this is so? Unable to find the right reading place on the WWW which explains the concept. Thanks for your

I am analyzing data from an experiment with two factors: Carbon (+/-) and O3 (+/-), with 4 replicates of each treatment, and 4 harvests over a year. The treatments are assigned in a block design to individual Rings. I have approaches this as a repeated measures design. Fixed factors are Carbon, O3 and Harvest, with Ring assigned as a random variable. I have performed repeated measures analysis

Dear All, I am trying to put some Confidence intervals on some regressions from a linear model with no luck. I can extract the fitted values using 'predict', but am having difficulty in getting at the confidence intervals, or the standard errors. Any suggestions would be welcome Cheers Guy Using Version 2.1.0 (2005-04-18) on a PC vol.mod3 <-

Greetings all, I am curious to know if either of these two sets of code is more efficient? Example1: ## t-test ## colA <- temp [ , j ] colB <- temp [ , k ] ttr <- t.test ( colA, colB, var.equal=TRUE) tt_pvalue [ i ] <- ttr$p.value or Example2: tt_pvalue [ i ] <- t.test ( temp[ , j ], temp[ , k ], var.equal=TRUE) ------------- I have three loops, i, j, k. One to test the all of

dear list, i am running a within-design ANOVA with 4 factors (4,4,2 and 2 levels each). the last one is a time factor comprising two different treatment timepoints. i fit a mixed-effects model using lme and apply the anova function to the outcome. according to this analysis, there are highly significant main effect on the first and the time factor. i then checked the boxplots for the two 4-level

And as follow up, fff<-function(x) gsub(",", ".", x) BX <- apply(apply(AX, 2, fff), 2, as.numeric) this seems to be easier. Cheers Petr S pozdravem | Best Regards RNDr. Petr PIKAL Vedouc? V?zkumu a v?voje | Research Manager PRECHEZA a.s. n?b?. Dr. Edvarda Bene?e 1170/24 | 750 02 P?erov | Czech Republic Tel: +420 581 252 256 | GSM: +420 724 008 364 petr.pikal at

Hi, I wonder whether R can finish the following project: I want to make a chart to represent 10 genes. Each gene has orientation and length. Therefore, a gene can be represented by arrows. Can R be used to draw 10 arrows in one line ? scott --------------------------------- [[alternative HTML version deleted]]

Hi. I have 2 tables, with same dimensions (8000 x 5). Something like: tab1: V1 V2 V3 V4 V5 14.23 1.71 2.43 15.6 127 13.20 1.78 2.14 11.2 100 13.16 2.36 2.67 18.6 101 14.37 1.95 2.50 16.8 113 13.24 2.59 2.87 21.0 118 tab2: V1 V2 V3 V4 V5 1.23 1.1 2.3 1.6 17 1.20 1.8 2.4 1.2 10 1.16 2.6 2.7 1.6 11 1.37 1.5 2.0 1.8 13 1.24 2.9 2.7 2.0 18 I need generate a table of averages, the

Dear All, Using:- R : Copyright 2005, The R Foundation for Statistical Computing Version 2.1.1 (2005-06-20), ISBN 3-900051-07-0 and Jose Pinheiro, Douglas Bates, Saikat DebRoy and Deepayan Sarkar (2005). nlme: Linear and nonlinear mixed effects models. R package version 3.1-65. on a WINDOWS 2000 machine I am trying to run the scripts from the Mixed Models book and am running into some

Hello together, Is there a tool to test the statistical differences between parameter estimates of a nlsList fit? I fitted degradation data using the nlsList method and want to find out whether derived rate constants are significantly different from each other at the grouping factors soil and temperature. Regards Frank Scherr

Hi all. I have an issue that I cannot resolve. I am trying to read in lots of data that are stored in xml files. But after I read them in and copy the relevant data, then remove the document etc, it doesn't free up the memory. When I monitor it in windows task manager the memory usage just climbs with each iteration until R crashes. I can replicate the problem with the small example:

Hi, It feels like I should be able to do something like: R CMD INSTALL lib='/usr/lib64/R/library' repos='http://proxy.url/cran' package We have a bunch of servers (compute nodes in a Rocks cluster) in an isolated subnet, there is a basic pass-through proxy set up on the firewall (the head node) which just passes HTTP requests through to our nearest CRAN mirror. when using

Hi, I have a three dimensional array, e.g., my.array = array(0, dim=c(2,3,4), dimnames=list( d1=c("A1","A2"), d2=c("B1","B2","B3"), d3=c("C1","C2","C3","C4")) ) what I would like to get is then a dataframe: d1 d2 d3 value A1 B1 C1 0 A2 B1 C1 0 . . . A2 B3 C4 0 I'm sure there is one function to do