similar to: Using data frame col names and variables

Dear All, I'm rather a beginner on nested ANOVAs, so here goes with my 2 questions; Qu 1: I'm modelling the number of galls on a leaf (the response variable) as a function of; the tree on which I find the leaf, the branch on which I find the leaf. Then, the tree and the branch are both random factors, and I'm quite happy that I should write; aov(galls~tree/branch +

Hello, I have tried to build ices both from CVS and from the latest tarball from the web site (using a varienty of configure options, or autogen.sh in the case of cvs). Whenever I try to run it I get errors: cadmium:/work/dl/Audio/streaming/ices-0.2.3 # /usr/local/icecast/bin/ices --help /usr/local/icecast/bin/ices: error while loading shared libraries: libgcc_s.so.1: cannot open shared object

Hi! I'm new to the list. I have a problem with mounting my home directory since my PC crashed. I hope that I can get some help on this list as I don't know much of ext3 myself. The mount command for my /home gives me the following output: # mount /dev/sda6 /mnt/tmp/ mount: wrong fs type, bad option, bad superblock on /dev/sda6, missing codepage or other error In some cases useful info

Wait. Now I'm really confused. > > head(samples) quant_samples age sapply(yo, toupper) E11.5 F20het BA40 E11.5 F20het BA40 E11.5 F20HET E11.5 F20het BA45 E11.5 F20het BA45 E11.5 F20HET E11.5 F20het BB84 E11.5 F20het BB84 E11.5 F20HET E11.5 F9.20DKO KTr3 E11.5 F9.20DKO KTr3 E11.5 F9.20DKO E11.5

Why doesn't this work? > samples$geno <- as.data.frame(sapply(yo, toupper), col.names="geno") > samples quant_samples age sapply(yo, toupper) E11.5 F20het BA40 E11.5 F20het BA40 E11.5 F20HET E11.5 F20het BA45 E11.5 F20het BA45 E11.5 F20HET

> On 24 Oct 2017, at 22:45 , David L Carlson <dcarlson at tamu.edu> wrote: > > You left out all the most important bits of information. What is yo? Are you trying to assign a data frame to a single column in another data frame? Printing head(samples) tells us nothing about what data types you have, especially if the things that look like text are really factors that were created

Hi Peter, Thanks for contributing such a great answer. Can you please provide a pointer to the documentation where it explains why dd$B <- s and dd["B"] <- s have such different behavior? (I am perfectly happy if you write the explanation but if it saves you time to point to some reference that works fine for me.) Regards, Eric On Wed, Oct 25, 2017 at 2:27 PM, Peter Dalgaard

#is there a way to get NA in the table of descriptive statistics instead of the function stopping Thank you in advance #data x.f <- structure(list(Site = structure(c(9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L), .Label = c("BC", "HC", "RM119", "RM148", "RM179", "RM185",

You left out all the most important bits of information. What is yo? Are you trying to assign a data frame to a single column in another data frame? Printing head(samples) tells us nothing about what data types you have, especially if the things that look like text are really factors that were created when you used one of the read.*() functions. Use str(samples) to see what you are dealing with.

Hi. I have a correlation matrix 'x' which is of size 923x923 I need to remove variables that are highly correlated. I don't have a sophisticated way of selecting which of the two in a highly correlated pair to remove. I thought I would just go through each entry of the correlation matrix and if it is greater than 0.6 (or less than -0.6) I will remove that column and then redo the

Dear R gurus, I have a very embarrassingly parallelizable job that I am trying to speed up with snow on our local cluster. Basically, I am doing ~50,000 t.test for a series of micro-array experiments, one gene at a time. Thus, I can easily spread the load across multiple processors and nodes. So, I have a master list object that tells me what rows to pick up for each genes to do the t.test from

Hi All I am looking for a way to prefix a constant value to all the rows in column in a data frame. Eg. V1 2 3 4 5 I want to make it like this V1 number2 number3 number4 number5 Thanks! -Abhi [[alternative HTML version deleted]]

Hello Gurus, I am still new to R. Here is my issue. I was trying to add column to data frame that was populated by read.spss(). When I used cbind to add a new variable(column). library(foreign) mydf<-read.spss(file="C:/myspss.sav",use.value.labels=FALSE, to.data.frame=TRUE,use.missings=FALSE) attr(mydf,"variable.labels") ## it gives you all the labels

Dear Maling list, I have a data.frame with three columns. I want to produce a fourth column which is result of "eliminating" the characters present in the second and third colum from the first. Example: a b c 1 ffff f f 2 hhhh j h 3 jjjj g g I want the result: ff hhh jjjj I can get what I want using the code

Say I have library(lattice) x<-runif(256) y<-runif(256) f<-gl(16,16) g1<-rep(1:4,each=64) g2<-rep(1:4,times=64) plot<-xyplot(y~x|f, groups=g1, pch=as.character(1:4), panel=function(x,y,subscripts,groups,...){ panel.superpose(x,y,subscripts,groups,...) }) print(plot) Currently, both

AdvisoRs: Is the following a bug, feature, hinky error message, or dumb Bert? > mtest <- matrix(1:12,nr=4) > dftest <- data.frame(mtest) > ix <- cbind(1:2,2:3) > mtest[ix] <- NA > mtest [,1] [,2] [,3] [1,] 1 NA 9 [2,] 2 6 NA [3,] 3 7 11 [4,] 4 8 12 ## But ... > dftest[ix] <- NA Error in `[<-.data.frame`(`*tmp*`, ix, value

Hi there! I'd like to make many tests and plots, for each variables. i.E. i <- 1 repeat { print (t.test(e[i], f[i])) i <- i + 1 if (i == 21) break } but the output is: Welch Two Sample t-test data: e[i] and f[i] ... so I don't know which data was calculated. Is there a way to tell the t.test or I'll make the same with plotmeans (from the gplots library)

> On Jun 21, 2017, at 9:11 AM, Evan Cooch <evan.cooch at gmail.com> wrote: > > Suppose I have the following sort of dataframe, where each column name has a common structure: prefix, followed by a number (for this example, col1, col2, col3 and col4): > > d = data.frame( col1=runif(10), col2=runif(10), col3=runif(10),col4=runif(10)) > > What I haven't been able to

Dear R list, I would like to perform an ANOVA in a set of measurements, but I have problems formatting the data. The data is a two dimensional array containing two columns: - "Stim" : the type of stimulation (string) - "Ratio" : a ratio of two numeric values Now, because some values are missing in the data (defaulting to zero), part of this array will be populated with NA

Hello, I'm attempting to evaluate the accuracy of the probability predictions for my model. As previously discussed here, the AUC is not a good measure as I'm not concerned with classification accuracy but probability accurcy. It was suggested to me that the loess function would be a good measure to look at. I can see some libraries (Design) will plot the loess function as a curve