similar to: zoo: new version 1.1-0

Dear useRs, the new version 1.2-0 of the zoo package for dealing with regular and irregular time series data is available from the CRAN mirrors. This version includes two important changes/enhancements: - rapply() was re-named to rollapply() because from R 2.4.0 on, base R provides a function rapply() for recursive (not rolling) application of functions, which was already described in

Dear useRs, yet another "new" package: zoo 0.2-0. zoo provides a simple S3 class and methods for totally ordered indexed observations such as irregular time series. Although there are other packages for irregular time series available on CRAN (Giles Heywood's its package and irts() in Adrian Trapletti's tseries package) I wrote this package because I needed something which

Dear useRs, yet another "new" package: zoo 0.2-0. zoo provides a simple S3 class and methods for totally ordered indexed observations such as irregular time series. Although there are other packages for irregular time series available on CRAN (Giles Heywood's its package and irts() in Adrian Trapletti's tseries package) I wrote this package because I needed something which

On Fri, 7 Apr 2006 16:09:53 +0200 Brandt, T. (Tobias) wrote: > Hi > > Is there a reason why as.matrix.zoo doesn't set the rownames to the > index like as.data.frame.zoo does? Yes, oversight, I think ;-) Added to the devel-version of zoo. I'll try to get it out to CRAN in the next days. Z > Thanks > > Tobias > > > > library(zoo) > > x.Date

Dear useRs, a new and much improved version of the zoo package for indexed totally ordered observations (such as irregular time series) is available from CRAN. It allows indexing observations with time/index vectors of arbitrary class and extends many of the standard generic functions also available for "ts" objects. Additionally, it allows conversion from/to other (irregular) time

Dear useRs, a new and much improved version of the zoo package for indexed totally ordered observations (such as irregular time series) is available from CRAN. It allows indexing observations with time/index vectors of arbitrary class and extends many of the standard generic functions also available for "ts" objects. Additionally, it allows conversion from/to other (irregular) time

I'm not sure I'm using appropriate tools for what I'm trying to do; a reason for my lack of certainty is that I'm encountering difficulty with what I thought would be fairly simple: labeling the X axis of my graphs with human-readable timestamps. I'm using R 2.12.1, running in a FreeBSD 8.2-PRERELEASE r218945 environment. As I mentioned in a previous note, I working with data

Dear list-reader, by running the following script: library(zoo) sessionInfo() search() packageDescription("zoo") data(EuStockMarkets) dax <- as.zoo(EuStockMarkets[1:10, "DAX"]) daxr <- diff(log(dax)) identical(as.vector(qnorm(daxr)), qnorm(coredata(daxr))) qqnorm(coredata(daxr)) qqnorm(daxr) qqnorm() produces an error: > qqnorm(daxr) Fehler in if (xi == xj) 0L

To the R development team; I found an unusual behavior in zoo when I upgraded to R 2.11.0 - it abruptly terminated when I performed certain operations on large zoo objects. I sent an e-mail to Achim Zeileis and he said this was a potential bug that I should report to the R development team. The details are given below in the thread below. Basically, I can crash R with this code: library(zoo)

Folks, I often build up R objects starting from NULL and then repeatedly using rbind() or cbind(). This yields code like: a <- NULL for () { onerow <- craft one more row a <- rbind(a, onerow) } This works because rbind() and cbind() are forgiving when presented with a NULL arg: they act like nothing happened, and you get all.equal(x,rbind(NULL,x)) or all.equal(x,cbind(NULL,x)).

Hi everyone and Achim, Achim, I appreciate your help about the function "NCOL". When I use "NCOL" instead of "ncol", I can find out the number of columns (number of time series) in the presence of only one time series (one variable, one column). Now I want to know how I can find out the column names of the zoo objects? In case of more than one time series, the

I believe that I have a basic understanding of zoo and how to use read.zoo on a text file, What I have not seen in the zoo help files and vignettes is how to convert a data frame to a zoo matrix for irregular time series analyses. An example data frame is structured like this: str(burns.cast) 'data.frame': 256 obs. of 47 variables: $ site : Factor w/ 143 levels

> Hello, > > I have lots of data in zoo format and would like to do some time > series analysis. (using library(zoo), library(ts) ) > > My data is usually from one year, and I try for example stl() to find > some seasonalities or trends. > > I have now accepted, that I might have to convert my series into ts() > but still I am not able to execute the comand since

I am the maintainer of its, but not it's original author. One of the main strengths of its is that it uses POSIXct dates. Zoo has the flexibility of using almost any date format, but I don't know if the other date formats can store hour, min, sec data. You might want to do a little exploring with each before you commit. I'll be happy to give you a hand if you decide to work with

I'm stuck, but am sure it can be done I just don't understand how. I have data in an irregular timeseries. I want to be able to use stl to visualise the data (see seasonal parts etc), so I need to change to regular series of class ts (I think). I am using 2 zoo objects one is regular and the other is my irregular data. I am then merging to create the object I want but when I try to change

Dear list, I have an irregular time series saved and exported as a zoo object. What is the trick to force zoo to ignore the missing dates when reading it back in? Thanks. > str(g) ?zoo? series from 1948-11-02 to 2012-11-06 Data: num [1:14881, 1:8] 1 0 0 0 0 0 0 0 0 0 ... - attr(*, "dimnames")=List of 2 ..$ : NULL ..$ : chr [1:8] "session" "midterm"

Hello, I'm trying to use na.spline (package zoo) to fill some missing data in a time series. this works fine, however, if I apply the 'maxgap' argument, I always get the error: <------ Error in na.spline.vec(x., coredata(object.), xout = xout., ...) : attempt to apply non-function ------> I couldn't find a similar error for this case in the mailing lists and zoo vignette,

Hi all I have an irregular zoo series, where the time index looks like the following: > head(time(l.zoo)) [1] "2009-06-15 01:44:20.802 GMT" "2009-06-15 01:44:20.812 GMT" "2009-06-15 01:44:20.837 GMT" "2009-06-15 01:44:20.848 GMT" "2009-06-15 06:00:01.320 GMT" [6] "2009-06-15 06:00:01.330 GMT" >

Hello, i would like to import this txt file: Giorno;PM10 2006-01-01 10:10;10.3 2006-02-02 20:22;50.3 2006-03-03 23:33;20.1 ......... As it's an irregular time series i use zoo as follow: require(zoo) z <- read.table("c:\\1.csv", sep=";", na.strings="-999", header=TRUE) q <- zoo(z$PM10, strptime(as.character(z$Giorno),"%Y-%m-%d %H:%M")) At this

I built some reasonably successful tools in a graphical database for reconstructing the developmental turning points for feedback loop driven natural processes. I'm trying to move it to R and am having difficulty with the very basics, i.e. a) defining time series using time as a natural number rather than a place in a table. I was also hoping b) someone might have built some of the