similar to: Reshape

Hello, helpeRs, I am attempting to reshape (either base R or package reshape) multiple .csv spreadsheets from a very unfortunate wide format to long format. ?Each spreadsheet looks something like this, after being read in to R: toy <- data.frame(year = rep(2007:2008,each = 20), month = rep(1:5,each = 4, length = 40), day = rep(1:2,each = 2,length = 40), hhmm = rep(1100:1101,length = 40),

Dear HelpeRs: I have a data set in the following format, which will be familiar to those of you working with NCDC climate data. Example: Year <- rep(1:3, each = 3) Year <- c(Year,Year) ID <- rep(1:2, each = 9) Jan <- runif(18, min = 0, max = 20) Feb <- runif(18, min = 0, max = 20) Mar <- runif(18, min = 0, max = 20) var <- gl(3,1,18,label =

I have a data frame that I created using read.table on a csv spreadsheet. The data look like the following: Steer.ID stocker.trt Finish.trt Date Days Wt ...... Steer.Id, stocker.trt, Finish.trt are factors------ Date, Days, Wt are data that are repeated 23 times (wide format). I want to reshape the data such that I have the correct Steer.ID, stocker.trt, Finish.trt identifying all of

Dear helpeRs, I have a dataframe (14947 x 27) containing measurements collected every 5 seconds at several different sampling locations. If one measurement at a given location is less than zero on a given day, I would like to delete all measurements from that location on that day. Here is a toy example: toy <- data.frame(CH = rep(3:5,3), DAY = c(rep(4,5), rep(5,4)), SLOPE =

I'm writing a package that interfaces to the FAME database, via a library of compiled C routines accessible through a Linux .so file. My .onLoad() function loads the .so like this: dyn.load("/opt/fame/timeiq/lib/linux_x86/libjchli.so", local = F) and after that I also load my own fame.so via library.dynam("fame", package = "fame") The code in fame.so uses

I would like to create a binary package for Windows which when installed will give the user an option of whether to install one version or another. Here is the problem, I have a package 'FAME' that can run in two different modes on Windows. An old mode that uses R to connect to a remote linux machine and a new way that uses a locally installed database. I would allow this decision to be

My fame package has a function that checks to see if a FAME SERVER process is already running. On Linux, I can do this in one of two ways: pid <- Sys.getpid() user <- Sys.info()["user"] cmd <- paste("pgrep -fU", user, "-P", pid, "'FAME SERVER'") fameRunning <- as.logical(length(system(cmd, intern = T))) or I can use cmd

Dear All, I wonder whether anyone has an experience with FAME package written by Jeff Hallman. All my attempts to send him the following problem report did not succeed (the mail system says that my e-mail could not be delivered), so I turn for help to this list. I tried to use your FAME package written for R, but somehow I cannot get it working. I am using Windows XP and the newest R

My fame package has to link to the libchli.so that comes with FAME. However, FAME is now supplying both 32 and 64 bit versions of the library. The 32-bit version is $FAME/hli/libchli.so while the 64-bit version is $FAME/hli/64/libchli.so. To set the right flags, it seems that I need to know, from within configure.ac, whether the R installation is 32 bit or 64 bit. Is there a way to detect this?

Hello list member: I've recently had a problem in that I'm unable to quit an R Session. I noticed this after the update to 2.8.0, but I believe I also noticed it on another machine, in the previous version. It occurs on both linux and Mac platforms. It only occurs when I start R in some particular workspaces that have alot of objects in them; it does not occur if I start R in an

Hello, R users, I have two factors (treat, section) anova design experiment where there are 3 replicates. The objective of the experiment is to test if there is significant difference of yield between top (section 9 to 11) and bottom (section 9 to 11) of the fruit tree under treatment. I found that there are interaction between two factors. I wonder if I can contrast means from levels of

I'm running an ANOVA on some data for respiration in a forest. I am having a problem with my degrees of freedom. For one of my variables I get one fewer degrees of freedom than I should. I have 12 plots and I therefore expected 11 degrees of freedom, but instead I got 10. Any ideas? I have some code and output below: > class(Combined.Plot) [1] "character" >

Dear R-list, I have a partly comma separated partly underscore separated string that I am trying to parse into R. Furthermore I have a bunch of them, and they are quite long. I have now spent most of my Sunday trying to figure this out and thought I would try the list to see if someone here would be able to get me started. My data structure looks like this, (in a example.txt file) Subject

Hello, R experts, I have a list called dataHP which has 30 elements (m1, m2, ..., m30). Each element is a 7x6 matrix holding yield data from two factors experimental design, with treatment in column, position in row. For instance, the element 20 is: dataHP[[20]] col1 col2 col3 trt1 trt2 trt3 [1,] 22.0 20.3 29.7 63.3 78.5 76.4 [2,]

Dear Thomas Lumley, and R-help list members, I have read your article "Network meta-analysis for indirect treatment comparisons" (Statist Med, 2002) with great interest. I found it very helpful that you included the R code to replicate your analysis; however, I have had a problem replicating your example and wondered if you are able to give me a hint. When I use the code from the

Dear, I have a dataset with 4 subjects (see ID in example), and 4 treatment (see TRT in example) which are tested on 2 locations and in 3 blocs. By using Lattice dotplot, I made a graph that shows the raw data per location and per bloc. In that graph, I would like to have a reference line per bloc that refers to the first treatment (T1). However, I can not find how to do that. I can make

Dear R - Users I have some problems fitting a linear mixed effects model using the lme function (nlme library). A sample data is as shown at the bottom of this mail. I fit my linear mixed model using the following R code: bmr <-lme (outcome~ -1 + as.factor(endpoint)+ as.factor(endpoint):trt, data=datt, random=~-1 + as.factor(endpoint) + as.factor(endpoint):trt|as.factor(Trial),

I am trying to define groupings from levels of factor variables and this the warning message that R give "& not meaningful for factors". The nature of my task is this. I have a variable stage which has the levels (1B, 2A, 2B) - these are the AJCC TNM stages of cancer, and another variable diameter with factor levels ("=< 4", "4 - 6.5, > 6.5; limit values are

I am confused whether Student's sleep data "show the effect of two soporific drugs" or Control against Treatment (one drug). The reason is the next: > require(stats) > data(sleep) > attach(sleep) > extra[group==1] numeric(0) > group [1] Ctl Ctl Ctl Ctl Ctl Ctl Ctl Ctl Ctl Ctl Trt Trt Trt Trt Trt Trt Trt Trt Trt [20] Trt Levels: Ctl Trt > sleep$group [1] 1 1 1 1 1

Hello, I have a problem with creating an identity matrix for glmnet by using the contrasts function. I have a factor with 4 levels. When I create dummy variables I think there should be n-1 variables (in this case 3) - so that the contrasts would be against the baseline level. This is also what is written in the help file for 'contrasts'. The problem is that the function