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Date:         Thu, 18 Oct 2007 10:32:21 -0500
Reply-To:     Warren Schlechte <Warren.Schlechte@TPWD.STATE.TX.US>
Sender:       "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From:         Warren Schlechte <Warren.Schlechte@TPWD.STATE.TX.US>
Subject:      Re: Method to distinguish different periods in time series data
Content-Type: text/plain; charset="us-ascii"

Following up on the Regime-Shift idea, that suggests quality-control and control charts could be a useful arena as well. There are both parametric and nonparametric constructs for cumsum and exponentially weighted moving averages (EWMA).

Warren Schlechte

-----Original Message----- From: Samuel Croker [mailto:samuel.croker@GMAIL.COM] Sent: Thursday, October 18, 2007 9:21 AM Subject: Re: Method to distinguish different periods in time series data

If you are pretty sure that you know when the change happened, then an intervention analysis is the way to go. I think that you should be able to find ample information on how this is done in the SAS/ETS documentation, particularly in PROC ARIMA, although only one of your variables can be the response at one time.

As to finding the change, the following link has a nice comparison of some of the methods of what they call "regime shift" detection - finding an unknown intervention in the data.

www.beringclimate.noaa.gov/regimes/rodionov_overview.pdf

It may spur some research ideas for you. There is a large amount of literature on this topic. I experimented with wavelet decomposition for anomaly detection and it was enlightening, but not particularly helpful for the problem that I was working on. "anomaly detection" is another good search phrase since it goes well beyond outlier detection, which can be problematic in this setting.

Sam

On 10/18/07, Warren Schlechte <Warren.Schlechte@tpwd.state.tx.us> wrote: > Seems to me a good starting point would be a loess fit. > > Final step seems like intervention analysis, although I believe there > you should have a known intervention. > > Hope these thoughts help. > > Warren Schlechte > > -----Original Message----- > From: kansaskannan@GMAIL.COM [mailto:kansaskannan@GMAIL.COM] > Sent: Wednesday, October 17, 2007 8:28 PM > Subject: Re: Method to distinguish different periods in time series data > > The variables are of unknown importance; I did make my initial > groupings based on graphs, but wondered if there was a better way. > > Thanks, Sam, for taking the time to respond. > > > On Oct 15, 10:02 pm, samuel.cro...@GMAIL.COM (Samuel Croker) wrote: > > I think that some good graphing can say a whole lot, and does not get > > into the potentially problematic area of doing statistical inference > > without thinking hard about it - always a dangerous area. Graphs can > > be helpful in getting your ideas together about next steps, and if > > done ethically and precisely they can be great descriptive tools to > > support your other analysis. > > > > Now you mentioned that you have several variables. Do you have a > > single target variable and the others potentially affect this one, or > > are all of the variables of equal or unknown importance? > > > > Sam > > > > On 10/15/07, kansaskan...@gmail.com <kansaskan...@gmail.com> wrote: > > > > > > > > > > > > > Thank you Sam. You are right, I am doing preliminary work to > determine > > > if there is indeed a shift in the phenomenon (home foreclosures) I > am > > > studying. I would like to find out if the number of foreclosures > has > > > changed significantly, and specifically when this change happened. > I > > > did do a t-test to compare two arbitrary periods, but wondered if a > > > different choice of periods would not also give me a significant > > > difference. I could repeat the process several times for different > > > pairs of arbitrary periods. I wondered if there were any SAS > > > procedures - hence the post in this forum - that I could use to > > > determine (a) whether there is a significant change; (b) when the > > > change happened; (c) whether there are more than two 'periods' that > > > can be identified. > > > > > 11:45 am, samuel.cro...@GMAIL.COM (Samuel Croker) wrote: > > > > A little more info might be helpful. It does not sound as if you > are > > > > trying to model yet, but conducting some preliminary data > analysis. > > > > Is this right? Are you trying to verify seasonality or are you > > > > looking for other types of shifts in the data? > > > > > > Sam > > > > > > On 10/15/07, kansaskan...@gmail.com <kansaskan...@gmail.com> > wrote: > > > > > > > I have a time series dataset (monthly data; 220 observations). I > need > > > > > to determine if I can distinguish different periods, based on > (a) > > > > > changes in one variable; (b) changes in two or three variables > taken > > > > > together. > > > > > > > I would appreciate any pointers in simple terms. > > > > > > > Thank you. > > > > > > -- > > > > Samuel T. Croker > > > > Lexington, SC & Bethesda, MD > > > > -- > > Samuel T. Croker > > Lexington, SC & Bethesda, MD- Hide quoted text - > > > > - Show quoted text - >

-- Samuel T. Croker Lexington, SC & Bethesda, MD


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