similar to: coercing "numeric" components of data frame to "factor" or "ordered"?

I've got a data frame that looks like this: subject foo bar 2 1.7 3.2 2 2.3 4.1 3 7.6 2.3 3 7.1 3.3 3 7.3 2.3 3 7.4 1.3 5 6.2 6.1 5 3.4 6.9 ... That is, I've got multiple rows per subject. I need to compute summaries within categories where the subject has the same number

I am writing some R code that generates some figures. I am primarily developing on GNU/Linux, but will ultimately run the code on Windows in order to get WMF files I can integrate in an existing document. The win.metafile() function, of course, doesn't exist in the GNU/Linux version of R. I am contemplating writing an abstraction layer that runs the right thing, but I need to know how the

I am generating some graphs (on GNU/Linux using R 1.5.x) for a PowerPoint presentation my boss is giving next week. He just tried cut/pasted a plot off of a PDF file I had created, but he complained that the fonts were too small and fuzzy, and that he couldn't change the background. I have been playing with png(bg=transparent), but I am not sure what appropriate height,width parameters and

Here is the summary on predict when using an arima0 object: The arima0 object must be based on a time series vector. That is; x <- ts(xm1, frequency=12, start=c(1975,1)) x.ar <- arima0(x,order=c(1,1,1)) predict(x.ar,n.ahead=3) Thanks so much to Prof. Brian Ripley and David Brahm and other! Sincerely, Erin Hodgess

I'd like to generate some plots like you'd see on the old "normal probability graph paper", like the first plot in: <http://www.itl.nist.gov/div898/handbook/eda/section3/normprpl.htm> except the horizontal scale would have 1%, 5%, 25%, 50%, 75%, 95%, 99%, or similar quantiles, with associated tick/grid lines. [still hunting around for a good example...] something like

I"ve got a data frame with a selection of columns I want to compute a rank-order correlation matrix from without disturbing the original data frame. foo[,c("a","b","d","f","g")] What I wanted to do, intuitively, was: > cor(rank(foo[,c("a","b","d","f","g")])) but rank in that context

I've got a set of data that are weighted by a largish integer (ranging from about 50K to 1.5 million). I'd like to plot CDF's for this data taking into account the weighting. What do you recommend? Thanks! -- Russell Senior ``The two chiefs turned to each other. seniorr at aracnet.com Bellison uncorked a flood of horrible

I have encountered the following problem: I need to extract from a list of lists equally named compenents who happen to be 'one row' data frames. a trivial example would be: a <- list(list( df = data.frame(A = 1, B = 2, C = 3)), list(df = data.frame(A = 4,B = 5,C = 6))) I want the extracted compenents to fill up a matrix or data frame row by row. the obvious thing to do seems: b

I want to write a function to take an argument as the response variable of a linear model, e.g. to do anova's across a list of variables, something like the following (except, of course, this doesn't work): function(x) { anova(lm(x ~ my.factor,data=my.data)) } The x in lm() above is getting evaluated at the wrong level. How can I make this work? -- Russell Senior ``The two

Hello. I have been browsing the R- manual and not seen any direct implementation of Factor analysis. Is there anyone out there who has run Factor Analysis with R? Thanks Michael -- Michael Preminger Forsker / Research Scientist Avdeling for journalistikk, bibliotek- og informasjonsfag / Faculty of Journalism, Library and Information Science H?gskolen i Oslo / Oslo College

I am writing a little abstraction for a series of tests. For example, I am running an anova and kruskal.test on a one-factor model. That isn't a particular problem, I have an interface like: my.function <- function(model,data) { print(deparse(substitute(data))) a <- anova(lm(formula,data)) print(a) if(a$"Pr(>F)"[1] < 0.05) { pairwise.t.test(???) }

Dear all, Coercing a logical vector to a numeric one is easy. The as.numeric function is used. However what do we use when we have a matrix or an array? Sumona

Dear R listers, I am trying to compute the mean of a dummy variable that is encoded as a factor. However, even though the levels of my factor are 0 - 1, when I compute the mean (after coercing the factor to be numeric), R changes 0 into 1 and 1 into yes, thus altering my expected result. Please, consider the following working example: pp <- rep(0:1, 10) pp <- factor(pp, levels=(0:1),

Dear R-helpers, It seems to me that a character zoo cannot be coerced to a numeric zoo. Below is a minimal example. Can someone tell me what I have done wrong? > z<-zoo(1:4,order.by=1:4) > coredata(z)<-as.character(coredata(z)) > str(z) ‘zoo’ series from 1 to 4 Data: chr [1:4] "1" "2" "3" "4" Index: int [1:4] 1 2 3 4 >

Hi there, I'm running R 2.0.0 on Windows 95. I'm trying to coerce a column of factors within a data frame to numeric. This is not a problem with a vector, but I can't find a way to index a column within a data frame to achieve this. All the examples from 'An introduction to R', 'S-plus 6 programmers guide', etc, use simple vectors. I'm sure I'm missing

Given a set of data: > names(data) [1] "city" "house" "visit" "value" I am looking for a way to compute the variance components of the nested model (ie, visit 1 at house 2 at city 3 isn't related to visit 1 and house 2 at city 4), but different houses in the same city may be related, and different visits to the same house are probably

Hello all, I have a very simple set of data and I would like to analyze them with probit analysis. The data are: X Event Trial 100 8 8 75 8 8 50 6 8 25 4 8 10 2 8 0 0 8 I want to estimate the value of X that will give a 95% hit rate (Event/Trial) and the corresponding 95% CI. Anyone can offer some help? Thanks!! -

Hi, I am not sure if this is a bug, so I am posting it here. I also searched the FAQ file for the readline string and did not find anything about the behavior below. I just successfully rsync'ed, compiled and tested R-1.4.0 on my RH 7.2 Linux machine. I encountered one problem though. When running ./configure I noticed that I was getting errors from the readline library. Although

I just ran into this strange behavior. y <- rnorm(1000) x <- seq(0, length=length(y)) plot(x, y, type='l', lty=1) - instantaneous plot(x, y, type='l', lty=2) - 18s plotting lines + 15s plotting axes = 33s plot(x, y, type='l', lty=3) - 76s ,, + 75s ,, = 151s plot(x, y, type='l', lty=4) -

Hi, I have a problem of estimating a mixture of two normal distributions. I need to find the starting points automatically, since this is a part of a larger piece of image processing code. I found the mix2normal1 function in VGAM package that mentions a method of finding starting values for mu1 and mu2 but refers the reader to a book by Everitt and Hand. Unfortunately, I do not have an easy