similar to: [?]apply functions or for loop

Hello, There has to be a more R'ish way to do this. I have two matrices, one has the values I want, but I want to NA some of them. The other matrix has binary values that tell me if I want to NA the values in the other matrix. I produce a third matrix based on this. I've also tried apply() passing in c(1,2) for rows and columns with no success yet. Example (this works, but I'm

Hello, I'm attempting to return the date (in form '%Y-%m-%d') of the Monday previous to the current date. For example: since it is 2011-09-02 today, I would expect 2011-08-29 to be the return value. I found the following in: http://www.mail-archive.com/r-help@r-project.org/msg144184.html Start quote from link: prevmonday <- function(x) 7 * floor(as.numeric(x-1+4) / 7) +

First I have a matrix called stocks1: > class(stocks1) [1] "matrix" Here are the first 5 rows of the last 4 columns: > stocks1[1:5,2:5] [,1] [,2] [,3] [,4] [1,] 80.73 31.95 25.4 25.69 [2,] 83.66 31.95 27.12 25.2 [3,] 83.27 32.93 28.74 26.29 [4,] 83.9 34.07 29.77 26.6 [5,] 82.74 35.18 30.24 27.41 Now, why can't I convert this into a dataframe?

Hello, which.max() only returns one index value, the one for the maximum value. If I want the two index values for the two largest values, is this a decent solution, or is there a nicer/better R'ish way? max2 <-function(v) { m=which.max(v) v[m] = -v[m] m2=which.max(v) result=c(m, m2) result } Seems to work ok. Thanks, Esmail

Dear all, I may have overlooked something but the following piece of code causes me trouble: > a_data.frame(1:4) > a X1.4 1 1 2 2 3 3 4 4 > apply(a,2,cat) 1 2 3 4Error in ans[[1]] : subscript out of bounds > apply(a,1,cat) 1234NULL Is this the fact my data.frame has only one dimension ? (and do I forget somewhere (but where ?) to specify not to 'drop'

I'm new to the R language and still struggling with compactness of R. I haven't got the right compass into the Documentation, too. So, please apologize the possibly stupidiy of my question. I have the following problem: I have two data sets combined in a data.frame x y 1.3 2.2 2.5 3.4 3.1 3.7 8.2 9.5 7.5 8.3 For the analyses of the data I want to group one column (like the classes in a

I have some data coming from SQL sources that I wish to relate in various ways. For reasons only known to our IT people, this can't be done in SQL at present. I am looking for an R'ish technique for looking up new columns on a data frame. As a simple, hardwired example I have tried the following: # This gives me two columns, one the lookup value and the second one # the result column,

I defined an S4 class with a slot i. Then I wrote a regular function that attempted to increment i. This didn't work, apparently because of the general rule that a function can't change the values of its arguments outside the function. I gather there are ways around it, but the Green book admonishes "cheating on the S evaluation model is to be avoided" (p. 190). Thinking that

Hi, If I add an entire disk to a new pool by doing "zpool create", is this reversible? I.e. if there was data on that disk (e.g. it was the sole disk in a zpool in another system) can I get this back or is zpool create destructive? Joubert This message posted from opensolaris.org

Hi everyone, I'm using the poLCA module for some analysis work. Basically, Im using the command >poLCA(f, data=response,nclass=2) This returns a poLCA object (a list) >From this data, I need to retrieve certain indexes, such as[[5]] as seen below. [[5]] Pr(1) Pr(2) Pr(3) class 1: 0 1.0 0.0 class 2: 0 0.5

Hello, I want to perform a latent class analysis using poLCA package. My formula is: substances <- cbind(subs1, subs2, subs3, subs4, subs5, subs6) ~ gender+age+education+income+occupation+urban+dbehavior+incarceration+treatment+depression+alcriteria I want to include sample weights in the model, I have read that poLCA does not take into account weights, but when I introduce them, it seems

Dear all, I've got a quite large dataframe (stor) with rows subject and rt (reaction time). I would like to split the reaction times per subject into 6 bins of equal size. Right now, I'm using the following code: bindata <- function(rt) { bindata <- rep(-1,length(rt)) binwidth <- length(rt)/6 bindata[order(rt)[(0*binwidth)+1:(1*binwidth)]] <- 1

Dear all, I'm an Sri Lankan undergraduate student. I'm also a total newbie to R. My aim is to use the poLCA package to do a latent class analysis. I found the documentation very helpful, but need to make a small clarification that has stumped me awhile. In my work, I need to make provision for conditional dependence. I'm told that poLCA lets you do that. Unfortunately, I

I need some help understanding a strange bridge performance problem I am seeing. Maybe I am making more out of this than I need to. I need your opinions. The setup: The first configuration is two machines connected via a cross over cable: Machine A <====> Machine B The second configuration is two machines with a Linux bridge between them: Machine A <===> Linux Bridge

What's the best approach to running latent class analysis with R? I've downloaded both randomLCA and poLCA packages, but I am interesting in running a standard LCA with individual records (not frequency table) as input data. Wen Gu John Jay College of Criminal Justice445 West 59 StreetNew York, NY 10029 wgu@gc.cuny.edu _________________________________________________________________

To those who will eb able to assist, Platform: On Ubuntu 12.04 I have used the latest Git version. I have installed isc-dhcp-server and bind9 from the plain apt repositories and have configured DHCP and BIND9 so that DHCP can update DNS entries via the hmac-md5 as so: key rndc-key { algorithm hmac-md5; secret "XXXXXXXXXXXXXXXXXXXX==";} allow unknown-clients; use-host-decl-names on;

Hi, I have a big data frame: > mat <- matrix(rep(paste(letters, collapse=""), 5*300000), ncol=5) > dat <- as.data.frame(mat) and I need to do some computation on each row. Currently I'm doing this: > for (key in row.names(dat)) { row <- dat[key, ]; ... do some computation on row... } which could probably considered a very natural (and R'ish) way of

Hi everyone? Does anybody know how can I estimate a Latent class multinomial (or conditional) logit using R? I have tried flexmix, poLCA, and they do not seem to support this model. thanks in advance adan -- View this message in context: http://r.789695.n4.nabble.com/Latent-class-multinomial-or-conditional-logit-using-R-tp4230083p4230083.html Sent from the R help mailing list archive at

Dear R users, I would like to perform Latent Class Logit Models for the analysis of choice experiments in environmental valuation. This kind of analysis is usually performed with NLogit Software (http://www.limdep.com). I attach the results I usually obtain using NLogit and NLogit model specifications. For Random parameter models and Logit Models I usually perform my analysis with the package

Hi, I am working with -poLCA- which uses the package -scatterplot3d- in order to work. However, I work on a restricted server that is not online. The R-version installed there is 2.6. However, running library(poLCA) after installing the most recent -scatterplot3d- on the server leaves me with R telling me that scatterplot3d needs R-version 2.7 or a more recent versions. Since I cannot install the