What strikes me is that, going by past modus operandi. The Hockey Team could leave out any set apart from the Bristlecone, and still get the results they wanted.

Now Moberg says he can leave out any one proxy and still be robust.

Looking at his graphs More on Moburg it appears that numbers 1 and 11 are very similar (HockeyStickish), and just leaving out one of them would still leave the other, to perform the same task as the Bristlecones did for Mann et al.

Therefor a good test would be to see if the results were robust leaving out any 2 Proxies, but particularly No’s 1 and 11.

it must be a pain to go through the data used by authors who don’t quite co-operate, regardless of their other attitudes.

But I also think that Moberg is not a member of the hockey team. He is just a climate scientist, so it just happens that he had to co-author with Mann, Jones, and others. But that does not mean that his approaches and conclusions are equal.

Incidentally, the Moberg graph itself does not really seem to show any visible anthropogenic influence, I think.

Happy Thanksgiving
Lubos

Danke for URL. Will read with my turkey (and think of the late great Tukey).

He certainly didn’t identify some obvious data irregulaties. Series 1 and 11 were not calibrated to temperature, are wildly non-normal and are the keys to keeping 20th century temperatures on a par with MWP temperatures. One of the most important Moberg proxies (and very non-normal) is the percentage of coldwater diatoms, an increased amount of cold sea water offshore Oman being held to be correlated with global warming and indeed one of the most essential proxies.

I think that you;ll be pretty amazed at the analysis of confidence intervals in the above URL. I’ll be interested in your thoughts.

To rephrase Steve McIntyre (if he will forgive me) the jackknife is the statistical technique of resampling by running the estimate on subsamples of N-q from a sample of N then averaging the results. It was introduce separately by Quenoulle (sp) and John Tukey 40-50 years ago. It was made popular in Mosteller and Tukey’s 1977 classic “Exploratory Data Analysis,” which is still a good book to read on practical statistics.

A similar technique called “bootstrapping” takes a random subsamples (usually of a given size) from the sample and runs the estimate on each subsample and then averages. Many econometric packages give code (scripts) for automating a bookstrap regression or similar procedures.

Bradley Efron’s (who Steve mentioned) little paperback book “The Jackknife, the Bookstrap and Other Resampling Plans” from the late ’70s or early 80s is clean and elegant introduction by a master.

Excellent point. I made a similar point on RC about the discovery process. If articles by Mann, Jones, et al are referenced by either the defence or the plaintiffs as part of the basis for a lawsuit, the discovery process will be far more persuasive and invasive than any of us could be requesting their data.

My comment on RC was muted, so that it would make it on to the site. It appears that any mention of missing data diverts your posting attempt to RC purgatory. This goes against the RC mantra is that all the data has always been available.