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. 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? Much appreciated, Jan ******************************************************* Jan Verbesselt Research Associate Lab of Geomatics and Forest Engineering K.U. Leuven Vital Decosterstraat 102. B-3000 Leuven Belgium Tel:+32-16-329750 Fax: +32-16-329760 http://perswww.kuleuven.ac.be/~u0027178/VCard/mycard.php?name=janv
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, ripley at stats.ox.ac.uk 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
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!stl() doesn't think so. What is the output of dim(Timeserie) or ncol(Timeserie) ? => The> problem is probably that this time series has to much noise so that it > consequently gives the following error.If the error message is correct, that's pretty unlikely. Have you run traceback() after the error message to find out where the problem occurred?> Error in stl(Timeserie) : only univariate series are allowed. I also > import the data as an ts object.How, exactly, did you import the data and convert to time series?> 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?This might be good practice, but doesn't sound like the solution to the problem.> Is the BISE (Best index slope extraction) function already programmed in > R I couldn't find it?Never heard of it. Jason -- Indigo Industrial Controls Ltd. 64-21-343-545 jasont at indigoindustrial.co.nz