similar to: Create matrices for time series

Hi list, based on the following data.frame I would like to create a variable that indicates the number of occurrences of A in the 3 years prior to the current year: DF = data.frame(read.table(textConnection(" A B 8025 1995 8026 1995 8029 1995 8026 1996 8025 1997 8026 1997 8025 1997 8027 1997 8026 1999 8027 1999 8028 1995 8029 1998 8025 1997 8027 1997 8026 1999 8027 1999

Hi, I have two lists (c and h - see below) containing matrices with similar cases but different values. I want to split these matrices into multiple matrices based on the values in h. So, I did the following: years<-c(1997:1999) for (t in 1:length(years)) { year=as.character(years[t]) h[[year]]<-sapply(colnames(h[[year]]), function(var)

Hi list, Can anyone tell my why the following does not work? Thanks a lot! Your help is very much appreciated. DF = data.frame(read.table(textConnection(" B C D E F G 8025 1995 0 4 1 2 8025 1997 1 1 3 4 8026 1995 0 7 0 0 8026 1996 1 2 3 0 8026 1997 1 2 3 1 8026 1998 6 0 0 4 8026 1999 3 7 0 3 8027 1997 1 2 3 9 8027 1998 1 2 3 1 8027 1999

Hi, I have produced a list g and I would like to reduce the amount of information contained in each object in g. For each matrix I would like to keep the values where the column name equals g[year][[1]][[x]] and the row names equals g[year][[1]][[-x]]. So in g$`1999`$`8029`, year = 1999 and x = 8029. I have been experimenting with the subset function, but have been unsuccesful. Thanks for your

Hi, I have a question concerning the selection of data. Let's say that given list h created below, I would like to select a section of the 1999 matrix. For a case (rownames and colnames) I would like to select the cells that have a value > 0. So for case 8025 8025 8026 8027 8025 1 1 1 8026 1 1 1 8027 1 1 1 And for case 8028 8028 8029 8028 1

Hi list, Using the script below, I have generated two lists (c and h) containing yearly matrices. Now I would like to divide the matrices in c into multiple matrices based on h. The number of matrices should be equal to: length(unique(DF1$B))*length(h). So each unique value in DF1$B get's a yearly matrix. Each matrix should contain all values from c where element cij is 1. An example for

Hi, I am trying to use the objects from the list below to create more objects. For each year in h I am trying to create as many objects as there are B's keeping only the values of B. Example for 1999: $`1999`$`8025` B B 8025 8026 8027 8028 8029 8025 1 1 1 0 0 8026 1 0 0 0 0 8027 1 0 0 0 0 8028 0 0 0 0 0 8029

Hi, I need to perform calculations on subsets of a data frame: DF = data.frame(read.table(textConnection(" A B C D E F 1 a 1995 0 4 1 2 a 1997 1 1 3 3 b 1995 3 7 0 4 b 1996 1 2 3 5 b 1997 1 2 3 6 b 1998 6 0 0 7 b 1999 3 7 0 8 c 1997 1 2 3 9 c 1998 1 2 3 10 c 1999 6 0 0 11 d 1999 3 7 0 12 e 1995 1 2 3 13 e 1998 1 2 3 14 e 1999 6

Hi, I have a data.frame of the following type: F = data.frame(read.table(textConnection(" A B 1 1 4 2 1 3 3 1 1 4 1 4 5 1 2 6 1 2 7 1 2 8 2 1 9 2 1 10 2 1 11 2 1 12 3 2 13 3 4 14 3 1 15 3 1 16 3 1"),head=TRUE,stringsAsFactors=FALSE)) F A B 1 1 4 2 1 3 3 1 1 4 1 4 5 1 2 6 1 2 7 1 2 8 2 1 9 2 1 10 2 1 11 2 1 12 3 2 13 3 4 14 3 1 15 3 1 16 3 1

Dear R users. I have zoo object "size_june" containing market-capital values: > dim(size_june) # market-cap data of 625 firms for 20 years [1] 20 625 > class(size_june) [1] "zoo" > size_june # colnames = "size.firmcode" size.34020 size.4710 size.11050 size.10660 size.9540 size.8060 size.16160 size.8080 size.9280 1988-06-30 NA

Hi Everybody, I'd like to start archiving e-mails by moving them to a server with running Dovecot. I installed "dovecot-core" and "dovecot-imapd" (version 2.3.4.1) on Debian 10. One of a few configurations I made is to use Maildir: # grep '^mail_location = ' /etc/dovecot/conf.d/10-mail.conf mail_location = maildir:~/Maildir I successfully moved some e-mails (at

Hi, I'm encountering a strange situation. I'm writing to an ext3 filesystem mounted like this: /dev/scsi/host2/bus0/target0/lun0/part3 on /tmp/volumes/md0 type ext3 (rw,noatime,data=ordered) with the physical device being a FC-connected RAID (IBM DF4000) no software raid personality is used I'm using 2.4.18-19.7 My test program writes files in a loop, with the essential system

I have a question about the Reduce function: x <- list() x[[1]] <- LETTERS[1:5] x[[2]] <- LETTERS[11:15] Reduce(paste, x) [1] "A K" "B L" "C M" "D N" "E O" How do I get this?: [1] "A" "K" [2] "B" "L" [3] "C" "M" [4] "D" "N" [5] "E" "O"

zoo's rollapply() function appears to be extremely useful for plugging in a function on-the-fly to run over a window. With inline, there is a lot more coding and room for error, and the code is less portable because the user has to have R compiling set up or it won't work. However, rollapply() seems to be really slow. Several orders of magnitude slower than inline, in fact. I don't

Hi I would like to understand how to extend the function (FUN) I am using in rollapply below. ###################################### With the following simplified data, test1 yields parameters for a rolling regression data = data.frame(Xvar=c(70.67,70.54,69.87,69.51,70.69,72.66,72.65,73.36), Yvar =c(78.01,77.07,77.35,76.72,77.49,78.70,77.78,79.58)) data.z = zoo(d) test1 =

Hi. I'm comparing output from rollapply.zoo, as produced by two versions of R and package zoo. I'm illustrating with an example from a R-help posting 'Zoo - bug ???' dated 2010-07-13. My question is not about the first version, or the questions raised in that posting, because the behaviour is as documented. I'm puzzled as to why na.rm no longer is passed to mean, i.e. why

Hi, I have the next procedure: t1<-data.frame(table(substr(names(subset(lasker[[1]], lasker[[1]] >= 4)), 1, 7))) t1[1:5,] Var1 Freq 1 1988-02 3 2 1988-03 1 3 1988-04 1 4 1988-05 2 5 1988-06 3 How to make a new list?, dataframe? having 189 elements in the 'lasker' list: > str(lasker[[1]]) 'table' int [, 1:1274] 1 1 3 2 1 5 4 1 1 4 ... -

Hi everyone, I have a rollapply statement that applies a function, in steps, over a data matrix as follows: #Code start testm<-rollapply(mat, 100, by=100, min, na.rm=F) #Code end This moves down matrix 'mat' and calculates the minimum value over a 100 row range, every 100 rows (i.e. no overlaps). NAs are not removed. I want to modify this statement somehow so that the rollapply()

Hi, Having a dataframe 'l1' (dput output is below): >dim(l1) 1274 2 >l1[1:12,] Var1 Freq 1 1988-01-13 1 2 1988-01-16 1 3 1988-01-20 3 4 1988-01-25 2 5 1988-01-30 1 6 1988-02-01 5 7 1988-02-08 4 8 1988-02-14 1 9 1988-02-16 1 10 1988-02-18 4 11 1988-02-24 2 12 1988-03-04 1 I want to extract the times

# Hi there, # I am trying to apply a function over a moving-window for a large number of multivariate time-series that are grouped in a nested set of factors. I have spent a few days searching for solutions with no luck, so any suggestions are much appreciated. # The data I have are for the abundance dynamics of multiple species observed in multiple fixed plots at multiple sites. (I total I