Abiel X Reinhart <abiel.x.reinh...@jpmchase.com> writes: > I have two identically sized matrices of data that represent time series (I > am storing the data in zoo objects, but the idea should apply to any matrix > of data). The time series in the second matrix extend further than in the > first matrix, and I would like to use the data in matrix 2 to extrapolate the > data in matrix 1. In other words, if mat1[i,j] == NA, then mat1[i,j] <- > mat1[i-1, j]*mat2[i,j]/mat2[i-1,j]. Of course, before we can calculate > mat1[i,j] we may need to calculate mat1[i-1,j], and that in turn may require > the computation of mat1[i-2,j], etc. This could all clearly be done with > loops, but I am wondering if anyone can think of a vectorized expression or > other efficient method that would work.
If you use tis objects and all of the columns of mat1 become NA on the same row, i.e., mat 1 looks like this: 20100101 1 2 3 20100102 4 5 6 20100103 NA NA NA 20100104 NA NA NA then something like this should work: mat1 <- naWindow(mat1) ## drops the ending NA rows rate <- growth.rate(window(mat2, start = end(mat1))) growth.rate(mat1) <- rate -- Jeff ______________________________________________ R-help@r-project.org 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.
