Dear all I hope there is somebody who encountered similar problem and can give me a hint how to do it or where to look.
I have several data sets in DBF format. I can transfer them to R data frames and then I want to perform aggregation or some other computations, but there are values in my data which I can call drop-outs and I want them to be discarded (see example). Usually I can find row of zeros (the measuring device is out of order or does not obtain any data) or a gradual decrease of some measured values due to real interruption of the process. I would like to do some evaluation (automatic) to set an logical vector where, for instance, TRUE will stay for "correct" values and FALSE will be for "drop-outs" (or vice versa). Preferably I would like to ***discard few values before and after actual drop-out occurred***. Then I will set all "wrong" values in my variables to NA and continue further computations. Here is some foo code for making artificial drop-outs similar like in my actual data x<-seq(0,100,.1) y<-sin(x)+rnorm(length(x),mean=0,sd=1) y1<-y-c(rep(0,200),exp(x[20:50]),rep(0,770)) y<-y1+50 y<-y*(y>0) y[600:700]<-0 My actual data looks like: Date, Time, Var1, Var2, Var3, ...... 01.01.01, 03:05:00, 12, 27, 0.53, ..... 01.01.01, 03:05:15, 12.2, 29, 1.2, ..... 01.01.01, 03:05:30, 12.2, 29, 0, ..... ......... in several data sets. I can simply put idx1<-y==0 I can set an arbitrary limit under or over which the value is considered a drop-out idx2<-y<45 and I can combine both indexes idx<-as.logical(idx1+idx2) But I do not know how easily enlarge the TRUE parts of index vector forwards and backwards the actual drop-out occurred. The only way how I am able to accomplish it is changes<-seq(along=x)[as.logical(diff(idx))]+1 than select odd an even values from changes subtract a certain value from odd and add a value to even and construct something like that c(rep(F,odd[1]),rep(T,even[1]-odd[1]),rep(F,odd[2]- even[1]),rep(T,even[2]- odd[2]),rep(F,length(x)-even[2])) what is a little bit complicated and not very general solution. Please can somebody help me find the better procedure or function for such drop- out filtering? Thank you. Petr Pikal Precheza a.s., Nabř.Dr.E.BeneÜe 24, 750 62 Přerov tel: +420581 252 257 ; 724 008 364 [EMAIL PROTECTED]; [EMAIL PROTECTED] fax +420581 252 561 ______________________________________________ [EMAIL PROTECTED] mailing list http://www.stat.math.ethz.ch/mailman/listinfo/r-help
