4

Suppose I have some time series. I already removed seasonality, so it consists of trend, some events and error.

I need to find the events, their length in periods,and their strength they had on the trend.

My idea is to divide data into several "windows", and calculate the length and strength

Do you know of a similar technique?

jonsca
  • 1,790
  • 3
  • 20
  • 30
Ivan Konanykhin
  • 41
  • 1
  • 4

1 Answers1

1

Ivan,

No. I will point you to the work of Tsay www.unc.edu/~jbhill/tsay.pdf‎

You might not have removed the seasonality properly. Did you look for seasonal pulses?

As for your outliers, there are outliers, there are level shifts, there are changes in trend as well as seasonal pulses. You need to run a tournament of models with different approaches where you might need to look for the outliers first and then seasonality. There could also be changes in parameters and variance that need to be tested for. Consider many many options.....post one data set here and perhaps we can do a deep dive?

Tom Reilly
  • 1,677
  • 11
  • 13
  • The link is dead. I searched for Tsay and he published several books and papers. Which work was actually referenced here? – RubenLaguna Jul 15 '16 at 14:40
  • 1
    http://onlinelibrary.wiley.com/doi/10.1002/for.3980070102/abstract Introductory Economics > Journal of Forecasting > Vol 7 Issue 1 > Outliers, level shifts, and variance changes in time series – Tom Reilly Jul 15 '16 at 14:46