similar to: Equivalent of Mathematica's Apply

Hi all, I would like to flag each record in the data according to certain conditions as specified below. For example, If "Close_date" in *dat* is between ("Open" & "Close") or ("Open1" & "Close1") or ("Open2" & "Close2") in *oc, *flag the records as "Valid", otherwise "Invalid" I would like to

Dear R-users, after trying and searching a long time i have the following question. is it possible to replace to following double loop by some apply calls? ####################################################################### m1 <- data.frame(v1=factor(letters[1:5]), v2=factor(letters[2:6]), v3=factor(letters[3:7])) m2 <-

Hello all. I've got a little file which is from S-Plus. The problem is I don't own a copy of said program, and R won't read it. I wonder if there's a caritative soul here who could export the file to some other format (csv, or even excel!) and send it back to me. Thanks in advance. Juan Pablo

Hello, The problem I'm working now requires to operate on big matrices. I've noticed that there are some packages that allows to run some commands in parallel. I've tried snow and NetWorkSpaces, without much success (they are far more slower that the normal functions) My problem is very simple, it doesn't require any communication between parallel tasks; only that it divides

Hi. I'm a real newbie in R, so I don't know how to apply, a function created by myself... prediction<-function(a,b) { .. } to a vector... It doesn't seem to understand lapply(vector, prediction())... Anyone can help me? Thanks in advance, ana

All, Is there one liner way to obtain the max per observation for two vectors? I looked at apply and lapply but it seems that groundwork would have to be done before applying either of those. The code below does it but seems like overkill. Thanks! Dave x = rnorm(10) y = rnorm(10) ind = which(x < y) z = x z[ind] <- y[ind] ## z now contains the max's

Dear all, I have a question on applying a function to the data according to factor levels. For example, for the data below, what is the best way to apply a function to "values" according to different levels of "samples" (1,2,3,4,5)? values ind sample 1 0.03325 1 1 2 0.03305 1 1 3 0.03185 1 1 4 0.03515 1 1 5 0.03375 1 1 6 0.01180

Dear R experts: Here is my problem, just hard for me... I want to generate multiple datasets, then apply a function to these datasets and output corresponding output in single or multiple dataset (whatever possible)... # my example, although I need to generate a large number of variables and datasets seed <- round(runif(10)*1000000) datagen <- function(x){ set.seed(x) var <- rep(1:3,

Hi All, Just hoping some one can give me a hand with a problem... I have a dataframe (DF) with about 5 million entries that looks something like the following: >DF ID Cl Co Brd Ind A AB AB 1 S-3 IND A BR_F BR_F01 1 0 0 2 S-3 IND A BR_F BR_F01 1 0 0 3 S-3 IND A BR_F BR_F01 1 0 0 4 S-3 IND A BR_F BR_F01 1 0 0 5 S-3 IND A BR_F BR_F01 1 0 0 6 S-3 IND A BR_F

Dear R users, I have the "any" function of R  any(ind.c, ind.r, ind.sgn) all are logical factors  it works fine when any of three is true but when they are combined it doesnt work. i tried this any(ind.c, ind.r, ind.sgn,((ind.c==TRUE) & (ind.r==TRUE)), ((ind.c==TRUE) & (ind.sgn==TRUE)),((ind.r==TRUE) & (ind.sgn==TRUE)),  ((ind.c==TRUE) & (ind.r==TRUE) &

Hi, I'm trying to understand if my journal is fragmented. Here's some output from `debugfs -R "stat <8>" /dev/sda3`: Inode: 8 Type: regular Mode: 0600 Flags: 0x0 Generation: 0 User: 0 Group: 0 Size: 104857600 File ACL: 0 Directory ACL: 0 Links: 1 Blockcount: 205016 Fragment: Address: 0 Number: 0 Size: 0 ctime: 0x3c0442fd -- Tue Nov 27

I' ve seen that several people are looking for a function that creates a barplot with an error indicators (I was one of them myself). Maybe you will find the following code helpful (There are some examples how to use it at the end): # Creates a barplot. #bar.plot() needs a datavector for the height of bars and a error #indicator for the interval #many of the usual R parameters can be set:

Hello, I am trying to plot time-series data with certain weeks highlighted using symbols. require(ggplot2) #plotting time series data timescale <- seq(as.Date("01/01/09","%m/%d/%y"), length.out=12, by=7) data.all <- data.frame( id = c(rep('111',12),rep('222',12),rep('333',12)), week=c(timescale,timescale,timescale),

I have the following lines of code: ind <- rollapply(GSPC, 200, mean) signal <- ifelse(diff(ind, 5) > 0 , 1 , -1) signal[is.na(signal)] <- 0 I never get a value of -1 for signal even though I know diff(ind , 5) is less than zero frequently. It looks like when diff(ind , 5) is less than zero, signal gets set to 0 instead of - 1. Any ideas why ? Here's some information on ind and

Hi everybody, I see a missed optimization opportunity in LLVM that GCC catches and I'd love to hear community's input. Here's the original C code: 1 char arr[2]; 2 char *get(unsigned ind) { 3 if (ind >= 1) { 4 return 0; 5 } 6 return &(arr[ind]); 7 } The variable `ind` is unsigned so, based on the comparison, if it is not greater or equals to one, than it is

I posted this question way down at teh end of another thread realted to an error in step, but that was stupid since it really is another matter altogether. I should have posted it separately, as I have now done. The code below creates a data.frame comprising three marginally noisy surfaces. The code below (including a fix courtesy of David Winsemius that avoids a step function error through use

Hi, I run a maanova analysis and found this message error: Error in ma.svd(X, 0, 0) : 0 extent dimensions I did a google search and found this: \item ma.svd: function to compute the sigular-value decomposition of a rectangular matrix by using LAPACK routines DEGSVD AND ZGESVD. \item fdr: function to calculate the adjusted P values for FDR control. I did a search for LAPACK and

I have a large dataset grouped by a factor and I want to perform a regression on each data subset based on this factor. There are many ways to do this, posted here and elsewhere. I have tried several. However I found one method posted on the R wiki which works exactly as I want, and I like the elegance and simplicity of the solution, but I don't understand how it works. Its all in the formula

------------------ >>>>> Henric Winell <[hidden email]> >>>>> on Wed, 21 Oct 2015 13:43:02 +0200 writes: > Den 2015-10-21 kl. 07:24, skrev Suharto Anggono Suharto Anggono via R-devel: >> Marius Hofert-4------------------------------ >>> Den 2015-10-09 kl. 12:14, skrev Martin Maechler: >>> I think so: the code above

Hi everybody, just a quick question that drives me crazy: Is it possible to "join" 2 logical vectors ? i.e. x<-4 ind <- 1:19200 pin <- c(0, rep(400, 48) * (1:48)) ind1<-((pin[j] + 1) <= ind) & (ind <= pin[j + 2]) ind2<-((pin[j+x] + 1) <= ind) & (ind <= pin[j+x + 2]) ind2 and ind1 give the right TRUE index #but I would like something like that