search for: tssourcediag

...Give then following code: ############################################################ # find STL Outliers by weight and append sh2, use Robust # this should allow the initial outliers to be filtered # this section may be commented out. ############################################################ tsSourceDiag <- stl(tsSource,s.window="per", robust=TRUE) # tsSourceIO <- which(tsSourceDiag $ weights < 1e-8) # # This is how to append run-time regessors for(z in tsSourceIO) { tmpname <-paste("PreIO",z,sep="") #COPY EOM REGRESSOR AS A TEMPLATE sh2[[tmpname]] <- s...

...' # # This appends the found IOs to the regressor table. Stepwise tends to # remove them later on. I needed a programtic way of removing useless # regressors for model verification since I would not know their names # if any are found ############################################################ tsSourceDiag <- stl(tsSource,s.window="per", robust=TRUE) # tsSourceIO <- which(tsSourceDiag $ weights < 1e-8) # # This is how to append run-time regessors for(z in tsSourceIO) { tmpname <-paste("PreIO",z,sep="") #COPY EOM AS A TEMPLATE sh2[[tmpname]] <- sh2[["...