Michael is totally correct. I work with a data frame that happens to have weeks associated with it. So, it looks like I would not really benefit from ts functionality... Dimitri
On Thu, Aug 4, 2011 at 11:37 PM, R. Michael Weylandt <[email protected]> wrote: > Yes, the stats package has a lag function, but it's not really appropriate > for the sample data Dimitri gave us: to wit, it's not of "ts" (time series) > class so lag doesn't know what to do with it and gives an error message. > Perhaps it's just that I never really took the time to get used to it, but > I'm not a fan of R's "ts" class > > And while I do endorse the use of time series objects over data frames when > appropriate, I'd suggest going for the xts class which has greater > functionality and it's default lag seems to have a more logical default: > lagging the series in xts moves the first data point back, while it moves it > forward in the ts class. > > I guess my point is: if Dimitri is working with the dates directly instead > of time series (as some of his other posts have suggested), he should stay > in the data frame type and use the lag I, Daniel, or Josh wrote: if he has > proper time series, he might as well jump right into xts. > > Michael Weylandt > > On Thu, Aug 4, 2011 at 7:57 PM, Ken H <[email protected]> wrote: >> >> Hey all, >> Correct me if I'm wrong but, the 'stats' package has a lag() function >> like so >> lagged.series=lag(series,number of lags wanted) >> Furthermore, I am pretty sure that lag( ) accepts negative lags:=> >> leads. >> lag(x,1)=> object of one lag, lag(x,-1) object with one >> lead. >> Hope this answers your question, >> Ken >> >> On Thu, Aug 4, 2011 at 4:19 PM, Dimitri Liakhovitski < >> [email protected]> wrote: >> >> > Thanks a lot for the recommendations - some of them I am implementing >> > already. >> > >> > Just a clarification: >> > the only reason I try to compare things to SPSS is that I am the only >> > person in my office using R. Whenever I work on an R code my goal is >> > not just to make it work, but also to "boast" to the SPSS users that >> > it's much easier/faster/niftier in R. So, you are preaching to the >> > choir here. >> > >> > Dimitri >> > >> > >> > On Thu, Aug 4, 2011 at 4:02 PM, Joshua Wiley <[email protected]> >> > wrote: >> > > >> > > >> > > On Aug 4, 2011, at 11:46, Dimitri Liakhovitski < >> > [email protected]> wrote: >> > > >> > >> Thanks a lot, guys! >> > >> It's really helpful. But - to be objective- it's still quite a few >> > >> lines longer than in SPSS. >> > > >> > > Not once you've sources the function! For the simple case of a >> > > vector, >> > try: >> > > >> > > X <- 1:10 >> > > mylag2 <- function(X, lag) { >> > > c(rep(NA, length(seq(lag))), X[-seq(lag)]) >> > > } >> > > >> > > Though this does not work for lead, it is fairly short. Then you could >> > use the *apply family if you needed it on multiple columns or vectors. >> > > >> > > Cheers, >> > > >> > > Josh >> > > >> > >> Dimitri >> > >> >> > >> On Thu, Aug 4, 2011 at 2:36 PM, Daniel Nordlund < >> > [email protected]> wrote: >> > >>> >> > >>> >> > >>>> -----Original Message----- >> > >>>> From: [email protected] [mailto: >> > [email protected]] >> > >>>> On Behalf Of Dimitri Liakhovitski >> > >>>> Sent: Thursday, August 04, 2011 8:24 AM >> > >>>> To: r-help >> > >>>> Subject: [R] Efficient way of creating a shifted (lagged) variable? >> > >>>> >> > >>>> Hello! >> > >>>> >> > >>>> I have a data set: >> > >>>> set.seed(123) >> > >>>> y<-data.frame(week=seq(as.Date("2010-01-03"), as.Date("2011-01- >> > >>>> 31"),by="week")) >> > >>>> y$var1<-c(1,2,3,round(rnorm(54),1)) >> > >>>> y$var2<-c(10,20,30,round(rnorm(54),1)) >> > >>>> >> > >>>> # All I need is to create lagged variables for var1 and var2. I >> > >>>> looked >> > >>>> around a bit and found several ways of doing it. They all seem >> > >>>> quite >> > >>>> complicated - while in SPSS it's just a few letters (like LAG()). >> > >>>> Here >> > >>>> is what I've written but I wonder. It works - but maybe there is a >> > >>>> very simple way of doing it in R that I could not find? >> > >>>> I need the same for "lead" (opposite of lag). >> > >>>> Any hint is greatly appreciated! >> > >>>> >> > >>>> ### The function I created: >> > >>>> mylag <- function(x,max.lag=1){ # x has to be a 1-column data >> > >>>> frame >> > >>>> temp<- >> > >>>> >> > as.data.frame(embed(c(rep(NA,max.lag),x[[1]]),max.lag+1))[2:(max.lag+1)] >> > >>>> for(i in 1:length(temp)){ >> > >>>> names(temp)[i]<-paste(names(x),".lag",i,sep="") >> > >>>> } >> > >>>> return(temp) >> > >>>> } >> > >>>> >> > >>>> ### Running mylag to get my result: >> > >>>> myvars<-c("var1","var2") >> > >>>> for(i in myvars) { >> > >>>> y<-cbind(y,mylag(y[i]),max.lag=2) >> > >>>> } >> > >>>> (y) >> > >>>> >> > >>>> -- >> > >>>> Dimitri Liakhovitski >> > >>>> marketfusionanalytics.com >> > >>>> >> > >>> >> > >>> Dimitri, >> > >>> >> > >>> I would first look into the zoo package as has already been >> > >>> suggested. >> > However, if you haven't already got your solution then here are a >> > couple of >> > functions that might help you get started. I won't vouch for >> > efficiency. >> > >>> >> > >>> >> > >>> lag.fun <- function(df, x, max.lag=1) { >> > >>> for(i in x) { >> > >>> for(j in 1:max.lag){ >> > >>> lagx <- paste(i,'.lag',j,sep='') >> > >>> df[,lagx] <- c(rep(NA,j),df[1:(nrow(df)-j),i]) >> > >>> } >> > >>> } >> > >>> df >> > >>> } >> > >>> >> > >>> lead.fun <- function(df, x, max.lead=1) { >> > >>> for(i in x) { >> > >>> for(j in 1:max.lead){ >> > >>> leadx <- paste(i,'.lead',j,sep='') >> > >>> df[,leadx] <- c(df[(j+1):(nrow(df)),i],rep(NA,j)) >> > >>> } >> > >>> } >> > >>> df >> > >>> } >> > >>> >> > >>> y <- lag.fun(y,myvars,2) >> > >>> y <- lead.fun(y,myvars,2) >> > >>> >> > >>> >> > >>> Hope this is helpful, >> > >>> >> > >>> Dan >> > >>> >> > >>> Daniel Nordlund >> > >>> Bothell, WA USA >> > >>> >> > >>> >> > >>> >> > >> >> > >> >> > >> >> > >> -- >> > >> Dimitri Liakhovitski >> > >> marketfusionanalytics.com >> > >> >> > >> ______________________________________________ >> > >> [email protected] mailing list >> > >> https://stat.ethz.ch/mailman/listinfo/r-help >> > >> PLEASE do read the posting guide >> > http://www.R-project.org/posting-guide.html >> > >> and provide commented, minimal, self-contained, reproducible code. >> > > >> > >> > >> > >> > -- >> > Dimitri Liakhovitski >> > marketfusionanalytics.com >> > >> > ______________________________________________ >> > [email protected] mailing list >> > https://stat.ethz.ch/mailman/listinfo/r-help >> > PLEASE do read the posting guide >> > http://www.R-project.org/posting-guide.html >> > and provide commented, minimal, self-contained, reproducible code. >> > >> >> [[alternative HTML version deleted]] >> >> ______________________________________________ >> [email protected] mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide >> http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. > > -- Dimitri Liakhovitski marketfusionanalytics.com ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
