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...asically creates the table from the two variables, divides each cell by the sum of the column to obtain percentage, does the median polish, and computes the median of some of the cells: >juste.polish<-function(data,w=rep(1,nrow(data))/nrow(data)) >{tableR<-table(data[,1],data[,2]) > tableP<-tableR > marg2<-apply(tableR,2,sum) > for (i in 1:nrow(tableP)) > {tableP[i,]<-100*(tableR[i,]/marg2)} >juste.medp<-medpolish(tableP) >median(c(juste.medp$residuals[dimnames(juste.medp$residuals)[[1]]=="e<60",1], > juste.medp$residuals[dimname...

Hi All , Could you please tell using which library ,Dickey-Fuller Test can be run? Thanks a lot __________________________________________________ [[alternative HTML version deleted]]

Short question: Is it possible to use statistical tests, like the Augmented Dickey-Fuller test, in functions with for-loops? If not, are there any alternative ways to scale measures? Detailed explanation: I am working with time-series, and I want to flag curves that are not stationary and which display pulses, trends, or level shifts. >df DATE ID VALUE2012-03-06 1

...g Inf 4: In max(x) : no non-missing arguments to max; returning -Inf > library(tseries) > adf.test(REVENUE,alternative="explosive",k=0) Error in NCOL(x) : object 'REVENUE' not found > adf.test(rev$REVENUE,alternative="explosive",k=0) Error in if (interpol == min(tablep)) warning("p-value smaller than printed p-value") else warning("p-value greater than printed p-value") : missing value where TRUE/FALSE needed > summary(ur.df(rev$REVENUE,lags=0,type="trend") + ) ############################################### # Augmented Dickey-...