similar to: strptime() bug? And additional problem in package "tseries"

Hi all; I've already send a similar e-mail to the list and Prof. Brian Ripley answered me but my doubts remain unresolved. Thanks for the clarification, but perhaps I wasn't clear enough in posting my questions. I've got a postgres database which I read into R. The first column is Timestamp with timezone, and my data are already in UTC format. An 'printed' extract of R

Hi Gabor and everybody; Thanks Gabor, with the alternative step you've told me the problem is resolved. Comparing the two procedures: Extract from the source 'character' data: > rain$ts[2039:2046] [1] "25/03/2000 22:00:00 UTC" "25/03/2000 23:00:00 UTC" [3] "26/03/2000 00:00:00 UTC" "26/03/2000 01:00:00 UTC" [5] "26/03/2000 02:00:00

Hola, # Hacemos el KED. Ver función "krige()": KED.rad <- krige( formula=pluvPcp~layer, # covariable -> radar locations=lluvia.rad.pluv.spdf, newdata=radarGrid, # podría ser cualquier objeto Spatial model=v.fit, # modelo de semivariograma. maxdist=Inf

Sale plano sí. Ya se que sin tener los datos y el código es un poco difícil, pero es que mis datos ocupan mucho, es imposible. Seguiré mirando por internet. Muchas gracias Rubén. Un saludo, > To: r-help-es en r-project.org > From: rubenfcasal en gmail.com > Date: Thu, 6 Aug 2015 14:21:47 +0200 > Subject: Re: [R-es] Duda interpolación (package ' gstat ') > > Hola

A new version of tseries (0.9-10) has been uploaded to CRAN. The new version contains the class "irts" for irregularly spaced time series. Irregular time series are basically time series where each observation (uni- or multivariate) has a time-stamp represented by an object of class "POSIXct". It provides some basic functionality such as reading and writing irregular time

A new version of tseries (0.9-10) has been uploaded to CRAN. The new version contains the class "irts" for irregularly spaced time series. Irregular time series are basically time series where each observation (uni- or multivariate) has a time-stamp represented by an object of class "POSIXct". It provides some basic functionality such as reading and writing irregular time

Hello R users, I'm a newby to R (and programming software at large) and I would need some help to sum up event data at discreet time and irregular time interval into a hourly frequency. Here is an example of my time series frame (irregular time-serie object - irts in the tseries package): time value 2008-12-19 19:11:03 GMT 1 2008-12-19 19:12:00 GMT 0 2008-12-19

I make quite a lot of use of irregular time-series, and had already spent a bit of time writing an 'its' class when the 'irts' class was released via the package 'tseries'. I have experimented with the 'irts' class, and have some practical issues with its use. In some applications of irregular time-series (in my case these are financial and econometric) there are

Hi All, I have a data set of daily measurements of river flow. I would like to create a "ts" object from this data. Here's a sample data set: date <- as.Date(c(1:300), format="%Y") year=as.numeric(format(date, format = "%Y")) month=as.numeric(format(date, format = "%m")) julianday=as.numeric(format(date, format = "%j"))

Hi R-list, I'm working with irregular time series (time series of climate data, daily data 365/6 days a year) and would like to create regular time series from them ( irts e.g. Rain <- irts(as.POSIXct(Climate[,1]),Climate[,5]) to ts e.g. test <- ts(x, start=c(1997,1), frequency=365) ) such that I can find where the gaps (lacking temperature data, ...) are and try

I thought r-help let you attach asci files but I don't think it does now so below is a sample of my data set. Thanks again. 09:40:08.5238,67.00,33 09:40:09.1968,67.00,2 09:40:09.7945,67.00,2 09:40:09.7975,67.00,2 09:40:09.8318,66.99,-3 09:40:17.6335,66.95,3 09:41:09.3393,66.95,6 09:41:11.1482,66.95,-1 09:42:07.4552,66.90,-5 09:42:12.5823,66.85,-5 09:42:14.4329,66.80,-2

I have some daily data and would like to apply some of the time series functions to it. I have read various notes in the help archive on this, the latest I found suggested that I need to use the irts class (Irregularly spaced time series) for daily data since a year does not divide into an integer number of days. I see why I would have to do that if I have gaps (e.g. only data on weekdays) but

On Sun, 24 Aug 2014, Silvia Pfeiffer wrote: > It's well possible there are bugs. I don't know when the code was last > updated. The last commit was in May, so it looks like it is being worked on... I've gone ahead and raised three bugs, one for the offset, one for more helpful error messaged, and one for subsequent streams of a given type needing different roles+names.

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

I have never worked with R before so I am sorry if this is a bad question but I've tried and tried ( all day ) and I can't figure this problem out. I have the code below and I included the data file as an attachment. The code works in term of reading in the data correctly but when the graph gets created, the xaxis is really strangely/incorrectly labelled. I have been trying to understand

Hi, I have a list which looks like this... > str(y) List of 10 $ : chr [1:4] "ABCD" "5" "0" "1" $ : chr [1:4] "DEF" "15" "1" "16" $ : chr [1:4] "AAA" "2" "17" "8" $ : chr [1:4] "SSS" "15" "25" "1" $ : chr [1:4] "III"

Hello I have daily S&P 500 from 1950 for which I would like to do some time series analysis in R. Could someone please show me an example of how to create a ts/ irts object for my data? Additionally, how do I create monthly subsamples of the data. I've experimented with the window function but haven't had any luck. Thank you Ian Confidential: This electronic message and

Hello, I'm trying to migrate from maildir++ to mdbox. The maildir++ is a leftover of our previous setup (was using courier) We have 3 virtuals servers for our +70000 accounts. Now, I'd like to use mdbox, so I'm trying using dsync for that. I setup a new virtual server, configured for mdbox. 1st, I tried a basic setup: I established a file with all my accounts (taken from LDAP)

Dear R-users, I have a complex line by xy-values (ordered by z). And I would like to get interpolated y-values on the positions of x = 0:600. How do I get the correct points? x=c(790,790,790,790,790,786,783,778,778,766,763,761,761,761,715,628,521,350,160,134,134,129,108,101,93,111,161,249,288,243,139,45,7)