I welcome this article. I think that when we do PCA, why should we be confined to using the mean where the textbooks say we should? It just stifles creativity. It gives a bad impression of statistics to our students. We should robustly go where robusters have gone before, and use whatever number appeals to our aesthetic sense. Personally, I always use the number 42. It just feels right. Others however take the first third of the series, and then use the mean of that. Some prefer the first two thirds. I think, if taking a proportion, it would be aesthetically preferable to use the golden ratio or some derivative of that. But to each his own.
Meanwhile, I am enormously pleased to read that the science is robust, the results have been gotten by several different researchers, and the earth is warming.
Or cooling, depending on the mean of which set of numbers you take.
I was participating as "Guy" in the discussion. I only found out about it once it started, I'm afraid. I believe there are interesting titbits there for anyone interested in the statistical approach to this field. It is good to see the ASA engaging on this issue, and I wish they were more prominent in doing so. Note that the moderator of the discussion, Richard Pierson, gave his email address for further correspondence: pierson@amstat.org
NB. I am a PhD student in statistics in the UK and a student member of the ASA. I have no academic involvement at this time with climate research.
Missed it, too bad, could have used a 'head's up'. I went to the blog entry discussing this, and posted this question. Sorry for involving Tamino again, but he was mentioned over there *again*. It's tiring.
"VS said: Your comment is awaiting moderation. Hi everybody,
Hmm, I missed this activity/thread.
A question to the ASA, just for the record:
“What’s the ASA’s take on the non-stationarity of the instrumental temperature record?”
You all know what that means, and you all know what it implies.
———-
Those mentioning Tamino might want to take a look at my reply to Tamino’s claims. As a matter of fact, I’m inviting the ASA to look at them as well.
"VS said: Your comment is awaiting moderation. Also, I would like to take this opportunity to invite *each and every* statistician/econometrician reading this to take a look at this post, and join the discussion with her or his expert opinion (be that critical or supportive). All intelligent review welcomed!
The debate in this thread has been going on for over month now. There are plenty of test results, monte carlo simulation results (with code) and specification diagnostics posted under that link. I know for a fact that a lot of people are following the discussion.
Furthermore, I believe that the questions adressed are *important*, and the implications for statistical analysis performed in climate-science *severe*.
Looking forward to everybody’s contributions!
Kind regards, VS
PS. Here’s how Josh the cartoonist ‘translated’ the contents of the discussion on Bart’s blog, in case you are in need of an ‘executive summary’
I asked what they thought of the climate scientists use of the "RE" statistic which they seem to have invented themselves. One of the statisticians said "the formula given does not make sense to me".
I was surprised to see Question 2 and the answer to it. The apparent refutation of Wegman in the NRC report relies on "numerous articles", but it appears that there is only one (Tellus 2007) and three others in preparation. Not what I would call numerous.
Strange, my last comment on their site has been stuck in moderation for 4 days.
---------------------
VS said: Your comment is awaiting moderation. Hi Francisco,
Thank you for your valuable comment!
I know (through MC and Stock (1994)) that the PP test has severe size distortions conditional on a ARIMA(3,1,0) w/o drift or ARIMA(0,1,2) w drift that, respectively, me and Breuch and Vahid found.
ADF with SIC/HQ selection is exact (but obviously doesn’t account for potential breaks, I hence also used ZA).
I’ll try to run the MC’s on Kim and Perron (2007) as well.
VS said: Your comment is awaiting moderation. Hi Steven,
If Grant Foster (a.k.a. Tamino) was actually a trained statistician, instead of a ‘home schooled’ civil engineer, you might actually have a point.
However, as the link in my first post here demonstrates, Foster doesn’t know how to test for stationarity (or a structural break, for that matter). One can infer a lack of formal training in statistics from this very piece of information.
In fact, I have yet to find any evidence of his statistics qualifications online (and no, ’self-proclamation’ is not evidence).
Best if people stick to what they know, don’t you think?
Kind regards, VS
PS. I did enjoy listening to his Bedlam Boys song while explaining to him why you can’t ‘prove’ that unit root testing ‘doesn’t work’ by performing a spurious regression on 34 observations (i.e. his second ‘debunkation’, entitled ‘Still Not’ .
Here’s the song in question: http://www.youtube.com/watch?v=mQIAT4Hh7Jc
Reader Comments (11)
I welcome this article. I think that when we do PCA, why should we be confined to using the mean where the textbooks say we should? It just stifles creativity. It gives a bad impression of statistics to our students. We should robustly go where robusters have gone before, and use whatever number appeals to our aesthetic sense. Personally, I always use the number 42. It just feels right. Others however take the first third of the series, and then use the mean of that. Some prefer the first two thirds. I think, if taking a proportion, it would be aesthetically preferable to use the golden ratio or some derivative of that. But to each his own.
Meanwhile, I am enormously pleased to read that the science is robust, the results have been gotten by several different researchers, and the earth is warming.
Or cooling, depending on the mean of which set of numbers you take.
I was participating as "Guy" in the discussion. I only found out about it once it started, I'm afraid. I believe there are interesting titbits there for anyone interested in the statistical approach to this field. It is good to see the ASA engaging on this issue, and I wish they were more prominent in doing so. Note that the moderator of the discussion, Richard Pierson, gave his email address for further correspondence: pierson@amstat.org
NB. I am a PhD student in statistics in the UK and a student member of the ASA. I have no academic involvement at this time with climate research.
Missed it, too bad, could have used a 'head's up'. I went to the blog entry discussing this, and posted this question. Sorry for involving Tamino again, but he was mentioned over there *again*. It's tiring.
"VS said:
Your comment is awaiting moderation.
Hi everybody,
Hmm, I missed this activity/thread.
A question to the ASA, just for the record:
“What’s the ASA’s take on the non-stationarity of the instrumental temperature record?”
You all know what that means, and you all know what it implies.
———-
Those mentioning Tamino might want to take a look at my reply to Tamino’s claims. As a matter of fact, I’m inviting the ASA to look at them as well.
http://ourchangingclimate.wordpress.com/2010/03/01/global-average-temperature-increase-giss-hadcru-and-ncdc-compared/#comment-1643
Hamilton, you might want to take a look at this book:
http://www.amazon.com/Time-Analysis-James-Douglas-Hamilton/dp/0691042896
All the best, VS"
Just for the record, I also added this:
"VS said:
Your comment is awaiting moderation.
Also, I would like to take this opportunity to invite *each and every* statistician/econometrician reading this to take a look at this post, and join the discussion with her or his expert opinion (be that critical or supportive). All intelligent review welcomed!
http://ourchangingclimate.wordpress.com/2010/03/01/global-average-temperature-increase-giss-hadcru-and-ncdc-compared/#comment-2740
The debate in this thread has been going on for over month now. There are plenty of test results, monte carlo simulation results (with code) and specification diagnostics posted under that link. I know for a fact that a lot of people are following the discussion.
Furthermore, I believe that the questions adressed are *important*, and the implications for statistical analysis performed in climate-science *severe*.
Looking forward to everybody’s contributions!
Kind regards, VS
PS. Here’s how Josh the cartoonist ‘translated’ the contents of the discussion on Bart’s blog, in case you are in need of an ‘executive summary’
http://www.cartoonsbyjosh.com/unit-root-presence_scr.jpg"
@VS: I'd hope that all expert opinion was critical, be it pro or con. :-)
Oops... 'translation' typo :) ... You're (obviously) correct dearieme... ;)
I asked what they thought of the climate scientists use of the "RE" statistic which they seem to have invented themselves. One of the statisticians said "the formula given does not make sense to me".
http://www.scribblelive.com/Event/Statisticians_Comment_on_Status_of_Climate_Change_Science
I was surprised to see Question 2 and the answer to it. The apparent refutation of Wegman in the NRC report relies on "numerous articles", but it appears that there is only one (Tellus 2007) and three others in preparation. Not what I would call numerous.
Strange, my last comment on their site has been stuck in moderation for 4 days.
---------------------
VS said:
Your comment is awaiting moderation.
Hi Francisco,
Thank you for your valuable comment!
I know (through MC and Stock (1994)) that the PP test has severe size distortions conditional on a ARIMA(3,1,0) w/o drift or ARIMA(0,1,2) w drift that, respectively, me and Breuch and Vahid found.
ADF with SIC/HQ selection is exact (but obviously doesn’t account for potential breaks, I hence also used ZA).
I’ll try to run the MC’s on Kim and Perron (2007) as well.
Again, thanks for the pointer
Best, VS
and another comment at ASA:
---------------------------------
VS said:
Your comment is awaiting moderation.
Hi Steven,
If Grant Foster (a.k.a. Tamino) was actually a trained statistician, instead of a ‘home schooled’ civil engineer, you might actually have a point.
However, as the link in my first post here demonstrates, Foster doesn’t know how to test for stationarity (or a structural break, for that matter). One can infer a lack of formal training in statistics from this very piece of information.
In fact, I have yet to find any evidence of his statistics qualifications online (and no, ’self-proclamation’ is not evidence).
Best if people stick to what they know, don’t you think?
Kind regards, VS
PS. I did enjoy listening to his Bedlam Boys song while explaining to him why you can’t ‘prove’ that unit root testing ‘doesn’t work’ by performing a spurious regression on 34 observations (i.e. his second ‘debunkation’, entitled ‘Still Not’ .
Here’s the song in question: http://www.youtube.com/watch?v=mQIAT4Hh7Jc
What is the basic concept of panel data and Analysis panel data