Hello everybody, I have high frequency commodity price data that I need to analyze. My objective is to not assume any seasonal component and just identify a trend. Here is where I run into problems with R. There are two main functions that I know of to analyze this time series: decompose() and stl(). The problem is that they both take a ts object type with a frequency parameter greater than or equal to 2. Is there some way I can assume a frequency of 1 per unit time and still analyze this time series using R? I'm afraid that if I assume frequency greater than 1 per unit time, and seasonality is calculated using the frequency parameter, then my forecasts are going to depend on that assumption. names(crude.data)=c('Date','Time','Price') names(crude.data) freq = 2 win.graph() plot(crude.data$Time,crude.data$Price, type="l") crude.data$Price = ts(crude.data$Price,frequency=freq) I want frequency to be 1 per unit time but then decompose() and stl() don't work! dim(crude.data$Price) decom = decompose(crude.data$Price) win.graph() plot(decom$random[2:200],type="line") acf(decom$random[freq:length(decom$random-freq)]) Thank you.