similar to: lapply across using multiple columns

Hi, I have a couple of aggregation operations that I don't know how to accomplish. Let me give an example. I have the following irregular time series time x 10:00:00.021 20 10:00:00.224 20 10:00:01.002 19 10:00:02:948 20 1) For each entry time, I'd like to get sum of x for the next 2 seconds

Hi, I have a list that contains about 100 elements. Each element contains the following matrix structure a b 1 1 4 2 2 5 3 3 6 I'd like to sum column b across all elements. I'm thinking of using lapply or sapply but cannot get it to work. Any help would be really appreciated. Thank you. adschai

Hi, I have the following string that I converted to a POSIXct: > a <- "2009-08-24 10:00:00.213" > a.p <- strptime(a,"%Y-%m-%d %H:%M:%OS") > as.double(as.POSIXct(a.p)) [1] 1251122400 I can't seem to get the decimal fraction of .213 out by casting to double or numeric. Is there anyway to make sure that POSIXct spits that out? Thank you. adschai

Hi, I have a matrix or data.frame (df). When I would like to check if a column named "x" exists, it becomes my habit to do the following: if (length(which(colnames(df)=="x"))>0) Is there any smarter way to do this? Thank you. adschai [[alternative HTML version deleted]]

Hi, When I define a new class (through setClass), members defined in representation argument doesn't seem to like a class. For example, if I do the following: setClass("NotWork",representation=(x="zoo")) It seems to me that representation members will take in only primitive type to R. Is there any way to stuff a class as a member in another class? Thank you. - adschai

Hi, I am trying to install package xts. I am using OPENSUSE 11 64 bit. When I invoke: install.pacakges("xts",dependencies=T) I received a lot of "ERROR: compilation failed for package" errors when R tries to install xts dependencies. I do not understand this behavior. I notice one thing. It complains. ERROR: compilation failed for package 'Hmisc' ** Removing

Hi, I'm using optim with box constraints to MLE on about 100 data points. It goes quite slow even on 4GB machine. I'm wondering if R has any faster implementation? Also, if I'd like to impose equality/nonequality constraints on parameters, which package I should use? Any help would be appreciated. Thank you. rc

I do not want to use histogram because I have more control over base graphs that R provide. I'm wondering if hist function provides a parameter that can set y axis as % of count instead of raw count? If not, I'd like to know how I can add text or line on histogram function? I don't like the idea of having to use raw coordinates to set text position. Thank you. adschai [[alternative

Hi - I read through dse package manual a bit. I'm not quite certain how I can use it to estimate a time varying coefficient regression model? I might pick up an inappropriate package. Any suggestion would be greatly appreciated. Thank you. rh

Hi, I'm running into a wall when trying to use the integrate function. I have the following setting: powerLaw2 <- function(x,l1,l2,c0,t0) { idx <- which(x <= 0); if (length(idx) > 0) { x[idx] <- 0; } xl <- (-l1+l2)*log(x/t0); L <- log(c0)-l1*log(x)-log(1+exp(xl)); L <- exp(L); return(L); } plCDF2 <- function(x,l1,l2,c0,t0) {

Hi, I'm a bit puzzled. I uses exactly the same code in RcppExamples package to try adding RcppFrame object to RcppResultSet. When running it gives me segmentation fault problem. I'm using gcc 4.1.2 on redhat 64bit. I'm not sure if this is the cause of the problem. Any advice would be greatly appreciated. Thank you. Rob. int numCol=4; std::vector<std::string>

Hi, I do not understand why after I called apply on a function that returns an xts (getIdvAdjSeries) it returns a matrix whose columns are just numeric value of time series in xts instead of a list of xts objects. Basically, I called the following: apply(matrix(tickers,ncol=1),1,FUN=getDivAdjSeries) getDivAdjSeries <- function(ticker) { seriesName <-

Hi - Classic question that I tried to look up online and couldn't find a clear answer. It seems that I can have R to act as a server. But I never know how this works. Would anyone please provide an example or introduction material where I can learn about this? I'm trying to build an environment where computation are distributed/delegated among different servers requested whenever I need.

Hi, I encounter a situation where I have a list whose element is a column matrix. Says, $'1' [,1] 1 2 3 $'2' [,1] 4 5 6 Is there fast way to collapse the list into a matrix like a cbind operation in this case? Meaning, the result should be a matrix that looks like: [,1] [,2] [1,] 1 4 [2,] 2 5 [3,] 3 6 I can loop through all elements and do

Hi, Sorry that I have many questions today. I am using svm function on about 180,000 points of training set. It takes very long time to run. However, I would like it to spit out something to make sure that the run is not dead in between. Would you please suggest anyway to do so? And is there anyway to speed up the performance of this svm function? Thank you. - adschai

Hi, I have a question around how to build data structure in R. I have to implement a tree structure of data. I'm wondering if R already has something like a tree where I can extend from or I need to start from scratch. If so, what would be the most effective way to represent parent and child node relationship? I realize that R is not based on pointer so it's quite a different paradigm for

Hi - I tried to get some answer before but there seems to have no one response. My question is that I have a class like below definition: setClass("DBManager", representation(channel="RODBC")) My purpose of the conn slot is to hold a channel to database connection which is returned by a command like: channel <- odbcConnect("DB", uid="user",

Hi,I have a result from polr which I fit a univariate variable (of ordinal data) with probit function. What I would like to do is to overlay the plot of my fitted values with the different intercept for each level in my ordinal data. I can do something like:lines(rep(intercept1, 1000), seq(from=0,to=max(fit),by=max(fit)/1000))where my intercept1 is, for example, the intercept that breaks between

Hi - I am using polr. I can get a result from polr fit by calling result.plr <- polr(formula, data=mydata, method="probit"); However, from the 'result.plr', how can I access standard error of the estimated coefficients as well as the t statistics for each one of them? What I would like to do ultimately is to see which coefficients are not significant and try to refit the

Hi, I am using tsls function from sem package to estimate a model which includes large number of data. Among its predictors, it has a nominal data which has about 10 possible values. So I expand this parameter into 9-binary-value predictors with the coefficient of base value equals 0. I also have another continuous predictor. The problem is that, whenever I run the tsls, I will get 'System