similar to: Hourly data with zoo

Hello, Can anyone explain the following behaviour? To me it seems a bug, but maybe it is intentional. It seems that a diff on a zooreg class that is not _strictly_ regular only considers those entries that are 'deltat' apart. In the following, diff on the zooreg class only returns values where the index was one second apart. The example replicates by dev code, but I've also tested

Hi, I'm trying to make a ts object that has both NA values and a frequency other than 1 (so I can use stl). I've tried all permutations I can think of, but cannot get the desired (expected?) results. The values live in x and the corresponding semi-regular time stamps are in t: > library('zoo') > z = zoo(x, order.by=t, frequency=24) > zzr = as.zooreg(z, start=0) > zr

I have a 43MB dataframe ( 5 variables) and I'm trying to summarize subsets of the data. I've RTFM ( not very clear) and looked at a variety of samples but cant seem to figure out how to make these functions work. A sample of what I want to do would be this: ids<-seq(1,50) years<-c(rep(5,10),rep(6,10),rep(7,10),rep(8,20))

Hi List, I have weekly sales observations for several products drawn via ODBC. Source data is available at https://www.dropbox.com/s/78vxae5ic8tnutf/asr.csv. This is retail sales data, so will contain seasonality and trend information. I expect to see 52 or 53 observations per year, each observation occuring on the same day of the week (Saturday). Ultimately I'm looking to feed these series

Hi, I'm really struggling with barplot I have a data.frame with 3 columns. The first column represents an "incident" type The second column represents a "month" The third column represents a "time" Code for a sample data.frame incidents <- rep(c('a','b','d','e'), each =25) months <- rep(c(1,2), each =10) times

Given a matrix of MxN want to take the means of rows in the following fashion m<-matrix(seq(1,80),ncol=20, nrow=4) result<-matrix(NA,nrow=4,ncol=20/5) result[,1]<-apply(m[,1:5],1,mean) result[,2]<-apply(m[,6:10],1,mean) result[,3]<-apply(m[,11:15],1,mean) result[,4]<-apply(m[,16:20],1,mean) result [,1] [,2] [,3] [,4] [1,] 9 29 49 69 [2,] 10 30 50 70

Given a long zoo matrix, the goal is to "sweep" out a statistic from the entire length of the sequences. longzoomatrix<-zoo(matrix(rnorm(720),ncol=6),as.yearmon(outer(1900,seq(0,length=120)/12,"+"))) cnames<-c(12345,23456,34567,45678,56789,67890) colnames(longzoomatrix)<-cnames longzoomatrix[1:24,] 12345 23456 34567 45678

Given a matrix of m*n, I want to reorder it as a vector, using a row major transpose. so: > m<-matrix(seq(1,48),nrow=6,byrow=T) > m [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [1,] 1 2 3 4 5 6 7 8 [2,] 9 10 11 12 13 14 15 16 [3,] 17 18 19 20 21 22 23 24 [4,] 25 26 27 28 29 30 31 32 [5,] 33 34 35 36 37

there are really two related problems here I have a 2D matrix A <- matrix(1:100,nrow=20,ncol =5) S <- matrix(1:10,nrow=2,ncol =5) #I want to subtract S from A. so that S would be subtracted from the first 2 rows of #A, then the next two rows and so on. #I have a the same problem with a 3D array # where I want to subtract Q for every layer (1-10) in Z # I thought I solved this one

Hi, I have a financial (zoo) time series with prices and volumes (although I can get the coredata as a matrix). Due to the data-source some indices have multiple observations. I want to aggregate these according to a weighted average. 11:00:01 34 1000 11:00:01 35 500 11:00:01 35 1000 11:00:02 34 500 11:00:02 35 500 should become 11:00:01 34.6 2500 11:00:02 34.5 1000 I currently do this

I've read the help and the archives on tryCatch but I'm still stuggling trying to understand how it works exactly and how I can use it to get the result I need. I have a data.frame of urls which point to 11 .zip files. Basically I use RCurl to get the list of files from a ftp and then reduce that directory dump to the 11 zip files I want to download. Its easy enough to do that in a loop

The situation arises where I open a file to write a data.frame to it. with write.table. multiple lines are written to the file and the file is kept in Append=TRUE mode. If one sets the col.names to the names of the variables being written, you have output that looks like this... name1 name2 name3..... x x x x x x x x x name1 name2 name

Assuming a data frame or matrix with two columns representing variable that you want to aggregate over. you want to calculate column means, by year, for each Id example<-data.frame(id=c(rep(12345,5),rep(54321,6),rep(45678,7)),Year=rep(seq(1900,1902,by=1),6), x=seq(1,18,by=1),y=seq(18,1,by=-1)) example id Year x y 1 12345 1900 1 18 2 12345 1901 2 17 3 12345 1902 3 16 4 12345

I was just rebuilding a package that has built before and I hit this error Error in loadNamespace(package, c(which.lib.loc, lib.loc), keep.source = keep.source) : cyclic name space dependency detected when loading 'GhcnDaily', already loading 'GhcnDaily' The package built just fine last revision, and the only changes I made were to Rd files How do I track this puppy down

Error in La.svd(x, nu, nv) : error code 1 from Lapack routine ‘dgesdd’ what resources are there to track down errors like this [[alternative HTML version deleted]]

The zoo package as a merge function which merges a set of zoo objects result<-merge(zoo1,zoo2,...) Assume your zoo objects are already collected in a list # make a phony list to illustrate the situation. ( hat tip to david W for constructing a list in a loop) ddat <- as.list(rep("", 20)) ytd<-seq(3,14) for(i in 1:20) { + ddat[[i]] <- zoo(data,ytd ) + } ddat [[1]] 1 2

In the particular application I have I save "test.Rdata" to a sub directory dir<-"Example" dir.create(dir) test<-data.frame(a=c(1,2,3),b=c(3,4,5) full<-file.path(dir,"test.Rdata,fsep=.Platform$file.sep) save(test,file=full) load(full) returns NULL it works fine when the object is saved to the working directory, but fails when saved to a sub directory. The Rdata

A quick question x <- as.yearmon(2000 + seq(0, 23)/12) x [1] "Jan 2000" "Feb 2000" "Mar 2000" "Apr 2000" "May 2000" "Jun 2000" "Jul 2000" "Aug 2000" "Sep 2000" "Oct 2000" "Nov 2000" "Dec 2000" "Jan 2001" [14] "Feb 2001" "Mar 2001" "Apr

I'm accessing around 95 tar files on an FTP server ranging in size between 10 and 40MB a piece. while certainly can click on them and download them outside of R, I'd like to have my script do it. Retrieving the ftp directory with RCurl works fine (about 90% of the time) but downloading the files by looping through all the files is a random process. I may get 1-8 files download and then

I have a matrix of zoo series. each series is in a column. x <- as.yearmon(2000 + seq(0, 23)/12) # 24 months of data, lets make 20 sets of random data testData <- matrix(rnorm(480),ncol=20) # make a zoo object and columns will hold the 20 series TestZoo <- zoo(testData,order.by=x) # now run lm for just one series. m <- lm(TestZoo[,1]~time(TestZoo))$coeff[2] m time(TestZoo)