Comments on: Spurious Significance #4: Phillips [1986]

By: VS

VS — Sat, 03 Apr 2010 16:33:28 +0000

Ah, forget it, found your e-mail address already

By: VS

VS — Sat, 03 Apr 2010 15:11:01 +0000

Steve, could you please send me a [blank or not] email?

Best, VS

By: TCO

TCO — Tue, 06 Sep 2005 17:29:06 +0000

boompity

By: TCO

TCO — Sat, 03 Sep 2005 22:57:21 +0000

Is the issue of run order, the same as the idea of autocorrelation? Should people doing manufacturing analysis use DW? Do they?

By: John S

John S — Sat, 27 Aug 2005 21:29:22 +0000

Steve,

I saw the article. My take is that they reached a solid but completely unremarkable conclusion – you can not treat temperature as a random draw from an iid distribution. He doesn’t account for any process that might drive temperature or lead to even cyclical variability (or, alternatively, they conclude that there is some process leading to fluctuations in temperature). That is, he concludes confidently (and I agree with him) that T(t) = e(t) is not a correct model for temperature (where e(t) represents draws from an iid distribution). But the universe of possibilities outside that is still rather large so it doesn’t get us a long way.

By: Steve McIntyre

Steve McIntyre — Sat, 27 Aug 2005 14:28:25 +0000

John S, did you see Benestad’s article at realclimate applying iid to climate series? His articles from which he draws do the same thing. It’s hard to comment on stuff like this without being acid.

By: mikep

mikep — Sat, 27 Aug 2005 13:33:25 +0000

TCO,
try this link

http://66.102.9.104/search?q=cache:wntz5IzG0cYJ:www.sussex.ac.uk/Units/economics/qm1/lectures/auto.doc+autocorrelation+time+OR+series+OR+econometrics+OR+simple+%22problem+of+autocorrelation+%22&hl=en

By: John S

John S — Sat, 27 Aug 2005 08:49:48 +0000

TCO,

You may not need DW etc but general advice is that you should be aware of the assumptions implicit in any regression or statistical technique you are running and be wary of situations where these might be violated. In whatever you are doing you should think about potential problems with your data and how these interact with the assumptions required for OLS (or whatever) to be correct. A common problem in econometrics is that the errors in a regression are not iid but are autocorrelated. I don’t know what common problems in crystalography, chemistry or manufacturing consulting are but they are undoubtedly there – identify what they are and make sure you are accounting for them. In general – a little knowledge is a dangerous thing.

By: TCO

TCO — Sat, 27 Aug 2005 05:10:33 +0000

So chemists don’t need ARIMA or DW. COOL! I can’t keep track of p and f and t tests as it is. Damn corporate six sigma crap!

Oh…and what about manufacturing consultants? Do they need to know DW?

And can you just include “run order” as a variable in the multiple regression from the DOE? Does that take care of autocorellation (I had never heard that term, concept before here…still not sure what it is.)

By: Steve McIntyre

Steve McIntyre — Sat, 27 Aug 2005 05:03:02 +0000

One of the things that I requested from Mann in Nov 2003 was his digital version of the 15th century reconstruction so I could calculate a DW statistic. This gets tied up in a long story about his submission to Climatic Change in 2004 which was rejected (although he cites in Jones and Mann 2004). Anyway even with the Barton stuff, we still don’t have Mann’s actual 15th century reconstruction. The Wahl-Ammann emulation is the same as mine and there are puzzling differences in the early portion. They don’t necessarily “matter” for whether it’s a hockey stick or not, but they sure could matter for calculating DW statistics. I’ve never figured out any validity to either Nature or NSF refusing to require Mann to produce output from which a DW statistic could be calculated for the 15th century proxies. Even Barton hasn’t got this.