On Wed, 30 Jul 2003, Jan Verbesselt wrote: > Dear R Helpers, > > Currently I'm working with the ts package of R and created a TimeSerie > from pixels extracted from satellite imagery(S10 NDVI data, 10 daily > composites). I'm trying to decompose this signal in different signals > (seasonal and trend). > > When testing out the STL method is says => Only univariate timeseries > are allowed, but the current Timeserie I'm using is univariate! => The > problem is probably that this time series has to much noise so that it > consequently gives the following error. > > plot(stl(Timeserie)) > Error in stl(Timeserie) : only univariate series are allowed. I also > import the data as an ts object.
No, the problem *is* that the time series is a matrix, and so not univariate. Try dim(Timeserie) to see. If it has one column (as I suspect), you need to remove that (dim(Timeserie) <- NULL). > A solution would be to eliminate the noise (sensor and atmospheric) with > a filter (kalman/ holt-Winters/TsSmooth? Or FFT.) or the BISE method in > R? > > Is the BISE (Best index slope extraction) function already programmed in > R I couldn't find it? I've never even heard of it. -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595 ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
