similar to: creating named elements of lists on the fly

I've noticed that R has a number of very useful functions for obtaining descriptive statistics on groups of variables, including summary {stats}, describe {Hmisc}, and describe {psych}, but none that I have found is able to provided weighted descriptives of subsets of a data set (ex. descriptives for both males and females for age, where accurate results require use of sampling

I have generated the following: x= E1 E2 E3 D1 0 0 1 D2 1 0 3 D3 0 2 0 y= E1 E2 E3 D1 0 0 1.75 D2 1.75 0 1.3125 D3 0 3.5 0 Where x and y are linked by: y =sum(x) * x / (rowSums(x)%o%colSums(x)) N=x[x[1:3,]>0] R=y[y[1:3,]>0] Now suppose I ONLY

Hello all, If someone could take a little time to help me then I would be very grateful. I studied piping plovers last summer. I watched each chick within a brood for 5 minutes and recorded behaviour, habitat use and foraging rate. There were two Sites, the first with 4 broods and the second with 3 broods. http://r.789695.n4.nabble.com/file/n4511178/Table_PP_Maslo_et_al.png As the data within a

Dear R-users, I did some more research and I'm still not sure how to set up an ANCOVA with nestedness. Specifically I'm not sure how to express chicks nested within boxes. I will be getting Pinheiro & Bates (Mixed Effects Models in S and S-Plus) but it will not arrive for another two weeks from our interlibrary loan. The goal is to determine if there are urbanization (purban)

Hi, In the examples from the ReShape package there is a simple example of using melt followed by cast that produces a smallish amount of output about the chicks database. Here's the code: library(reshape) names(ChickWeight) <- tolower(names(ChickWeight)) chick_m <- melt(ChickWeight, id=2:4, na.rm=TRUE) DietResults <- cast(chick_m, diet + chick ~ time) DietResults My challenge

according to the documentation of the cast function in the reshape function, I would expect this bit of code from the examples to calculate marginal means over only the 'diet' variable. #Chick weight example names(ChickWeight) <- tolower(names(ChickWeight)) chick_m <- melt(ChickWeight, id=2:4, na.rm=TRUE) cast(chick_m, diet + chick ~ time, mean, margins="diet") But,

Dear R-listers, I would like to know if there is a way to programmatically generate parameter start values for the model y~(a*exp(b*x)+c*exp(d*x)) in R. I've scoured the help files and archives for nls() and similar searches, and have read Fox 2002 - the best advice has been to make estimates from a priori knowledge of the data. However, in the Matlab CurveFit tool, reliable start values are

Hi R experts, I am interested on the effects of two dietry compunds on the growth of chicks. Rather than extracting linear growth functions for each chick and using these in an analysis I thought using ReML might provide a neater and better way of doing this. (I have read the pdf vignette("MlmSoftRev") and "Fitting linear mixed models in R" by Douglas Bates but I am not

Dear R-experts, Quite new to R on this end, but learning fast (I hope). I am running version 2.7.1 on Windows Vista. I have small dataset which consists of: # NestID: nest indicator for each chicken. Siblings sharing the same nest have the same nest indicator. # Chick: chick indicator consisting of a unique ID for each single chick. # Year: 1, 2. # ClutchSize: 1-, 2- , 3-eggs. # HO:

samba-3.0.10-1.4E on RHEL4-AS. I've got a test domain setup and working just fine. Windows XP clients are authenticating just fine. The only problem I have so far is my domain browser list is not correct. I can see everything in my subnet fine, but can't see anything outside my subnet. This is different than my NT4 domain, who's browse list shows me every domain within the larger

Hi All, I want to automatically generate a number of data frames, each with an automatically generated name and an automatically generated number of rows. The number of rows has been calculated before and is different for all data frames (e.g. c(4,5,2)). The number of columns is known a priori and the same for all data frames (e.g. c(3,3,3)). The resulting data frames could look something like

Dear R-users, I set up an experiment where I put up bluebird boxes across an urbanization gradient. I monitored these boxes and at some point I pulled a feather from a chick and a friend used spectral properties (rtot, a continuous var) to index chick health. There is an effect of sex that I would like to include but how would I set up a regression and look at the effect of urbanization

I just had a manuscript returned with the biggest problem being the analysis. Instead of using principal components in a regression I've been asked to analyze a few variables separately. So that's what I'm doing. I pulled a feather from young birds and we quantified certain aspects of the color of those feathers. Since I often have more than one sample from a nest, I thought I

Estimado Oliver Nuñez Envío un ejemplo reproducible. Javier Marcuzzi # de donde tomo datos, y tiene el modelo (en el pdf) library(MCMCglmm) # librería con las funciónes que voy a usar library(nlme) datos0<-ChickWeight # creo algunos datos que agrego a los origonales Factor<-as.numeric(datos0$Chick) Factor[Factor > 0 & Factor <= 10] <- 'A' Factor[Factor > 10

Dear R-experts, I am running R version 2.7.1 on Windows Vista. I have a small dataset which consists of ?chick ID?, ?year (0, 1)?, ?hatching order [HO, defined as first, second and third-hatched chick]?, and the binary outcome of interest ?death (0, 1)?. So a subset of my dataset looks like this on a txt file: y ID Yr HO 1 1 1 First 0 2 1 First 0 3 1 Second 0 4 1 First 1 5 1 First 0 6 1 Third

This patch implements persistent grants for the xen-blk{front,back} mechanism. The effect of this change is to reduce the number of unmap operations performed, since they cause a (costly) TLB shootdown. This allows the I/O performance to scale better when a large number of VMs are performing I/O. Previously, the blkfront driver was supplied a bvec[] from the request queue. This was granted to

I am aware that it is easily possible to create var names on the fly. e.g. assign(paste("m",i,sep=""),j) but is it possible to assign dataframes to variables created on the fly? e.g. If I have a dataframe called master and I wanted to subset parts of those data into separate dataframes, I could do: m1=subset(master,master$SAMPLE=='1')

Hello R-Group I found how to fill the data.frame -> http://finzi.psych.upenn.edu/R/Rhelp02a/archive/70843.html N1 <- rnorm(4) N2 <- rnorm(4) N3 <- rnorm(4) N4 <- rnorm(4) X1 <- LETTERS[1:4] ################### nams <- c(paste("N", 1:4, sep = ""), "X1") dat <- data.frame(lapply(nams, get)) names(dat) <- nams dat But I need also to create

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I have a rectangular matrix of size 920 by 85. I'd like to coerce it into a square matrix such that all row/col names are present in the new matrix and the additional values are zero. As an example: A B C D A 1 2 3 4 E 5 6 7 8 F 9 10 11 12 Would be coerced to: A B C D E F A 1 2 3 4 5 9 B 2 0 0 0 6 10 C 3 0 0

does anyone know how to get ksh to use tab completion? -- Andrew Rice Jr Systems Analyst Carrier Management Systems, Inc. 500 Chestnut Street, Suite 500 Abilene, TX 79602 USA support: (325) 672-0975 office: (325) 677-5900 fax: (325) 676-0529 http://www.nams.net NAMS III, NAMS 2000 Centralized, NAMS BMX