I have collected temperature readings for 4 locations on a beach in Cornwall UK using data loggers. The loggers recorded temperature every 15 mins accurate to .1 of a degree (Celsius). The loggers collected data for 10 days with a one day break to calibrate the sensors. In total I used 30 sensors with 6-7 sensors in each position.
I have now downloaded the data and have produced time-series for temperature over the 10 day period. Visual inspection of the time-series shows how the temperature changes with tides and night and day. I want to investigate whether the time-series differ significantly from one another. Please could someone point me in the direction of a technique to do this in SPSS?
Best Answer
To compare two time series simply estimate the COMMON appropriate arima model for each time series separately AND then estimate it globally ( putting the second series behind the first ) . Make sure that your software recognizes the beginning of the scond series and doesn't forecast it from the latter values of the first series. Perform an F test ala G. Chow to test the hypothesis of a common set of parameters. AUTOBOX , a program that I am involved with allows this test to be performed. SPSS may not.