I’m sure The Who anticipated trolls. Also add the lyrics: “Don’t try to dig what we all s-s-s-say. We’re just tryin’ to start a big s-s-s-sensation” (with apologies to Pete and the boys’ “Talkin’ ’bout My Generation)
What’s your point, troll? Hansen has blue eyes? So what, so do I and a lot of other people. Your “humor” escapes me.
OTOH, we all know that daveburton’s eyes are brown because he is a walking demonstration of the old saw about “His eyes are brown because he’s so full of ****”.
(Or is my saying that one of those “vicious” things that Dave alleges others have done but won’t give details about, even when asked repeatedly to do so?)
From the “How it’s Done. Mann v. Morano” thread below
Burton said,
One of the questions at issue is whether or not there really was a hockey-stick signal in the tree rings, at all.
Gee, why didn’t McIntyre/Wegman think about answering that question *before* they went running around making claims about “random noise” hockey sticks? Why didn’t McIntyre think about answering that question *before* he testified in front of Congress about Mann’s supposed “random noise hockey-sticks”? Why didn’t Wegman think about that *before* he submitted his report to Congress?
And why didn’t anyone else in the denier community think about investigating that question?
The above question is a question that should have been answered *before* McIntyre/Wegman blindly used the tree-ring data as a noise template. And it should have been answered *before* they told Congress that Mann’s method makes hockey sticks out of random noise.
The very first thing any *competent* analyst would do before said analyst used tree-ring data as a noise model would be to *look at the data* to determine whether there is low-frequency “hockey stick” climate signal that needs to filtered out.
No competent analyst would blindly assume that there’s no signal in the data
And yes, even a crude non-area-weighted average of the data will reveal an underlying “hockey-stick” pattern — it’s noisy, but it’s there. That pattern is clearly a very low frequency signal with a correlation time that is significant relative to the data length. It is quite visible, and very obviously must be filtered out.
Long correlation times relative to the length of your data will greatly increase the likelihood of producing spurious (false) trends, for reasons that are explained in any Time Series Analysis 101 course.
Taking raw, unfiltered tree-ring chronologies and blindly using them as a noise model without first looking to see what is actually in them is a colossal blunder.
Folks, this whole “Mann’s method makes hockey sticks from random noise” business is a perfect example of ideologically-driven incompetence. Incompetence that is rife in the denier community.
caerbannog666, there’s a question awaiting you over there.
caerbannog666 wrote, “Taking raw, unfiltered tree-ring chronologies and blindly using them as a noise model…”
I think you must at least suspect that such a mistake actually was not made by three highly credentialed PhD statisticians:
The Bernard J. Dunn Professor of Statistics at George Mason University, a Fellow of the American Statistical Association, past chair of the U.S. National Research Council’s Committee on Applied and Theoretical Statistics, and former president of the International Association for Statistical Computing.
And,
The Noah Harding Professor of Statistics, and Chair of the Department of Statistics at Rice University.
And,
A Research Professor from the National Institutes of Health at George Mason University, a Visiting Fellow at the Isaac Newton Institute for Mathematical Sciences at the University of Cambridge in England, and Co-Director of the Center for Computational Data Sciences in the College of Science at George Mason U.
What are your statistics creds, caerbannog666?
And have you actually read the 91-page Report of which you are so critical?
If you are certain that those statisticians did not make the mistake that I described, then please point out the lines in the above R script where they test the tree-ring data for the presence of a low-frequency climate signal (aka “hockey stick”) and then remove that signal from the tree-ring data before they use the tree-ring data as a model for their synthetic random noise.
(Unless the low-frequency signal is removed, the resulting synthetic noise model will be useless for generating true “noise-only” results.)
To make the code easier to navigate, I suggest copy/pasting it into an “R-aware” editor and using that editor’s syntactic highlighting and auto-indentation features to make the code easier to read through.
Two engineering degrees from the University of California: a BS in engineering, and an MSEE with an emphasis on communication-theory/stochastic-processes/detection-theory.
As for the Wegman Report — I’ve read the portions relevant to the material that I’ve been critical of here.
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So you have no formal statistics creds, but with your background you should be able to learn such topics, with sufficient work.
It is surprising to me that someone with a background so very similar to my own does not “get it.” Some folks here just don’t have the “tools” to understand the topics, but you should. So why don’t you?
For instance, most engineers would look at Muller’s criticism of Mann’s fraud and understand it, and be properly outraged at Mann’s fraud. But you aren’t. Most engineers would look at these graphs of sea level and immediately recognize the disconnect between the data and the alarmists’ claims. But you don’t.
You’re a lot like Peter. Apart from his excellent taste in music, he’s wrong about almost everything. Climate alarmists seem to filter out any information that conflicts with their prejudices, no matter how compelling, and latch onto even the flimsiest of evidence that confirms those prejudices.
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It is surprising to me that Dave actually thinks caerbannog666 has “a background so very similar to his”. And he then chastises him for “not getting it”? And Peter “is wrong about almost everything”?. And “Climate alarmists?”
I have said it before, but it bears repeating. Dave is shameless. And a distraction (AND a poison to the Crock community). If Dave had worked for me back in the day, he would be collecting unemployment benefits long ago.
It’s reformatted a bit and emphasis has been added (if I didn’t mess up the tags).
Note that it confirms exactly what I have been saying here — that the McIntyre/Wegman noise model was badly contaminated with “hockey stick” signal statistics.
Dear Dr Wegman and colleagues,
I am forwarding below an e-mail I sent you and
your colleagues requesting essential, but missing,
basic, information relative to your report to
Congress.
To facilitate a reply I attach the
Auto-Correlation Function used by the M&M to
generate their persistent red noise simulations
for their figures shown by you in your Section 4
(this was kindly provided me by M&M on Nov 6
2004).
The black values are the ones actually used by
M&M. They derive directly from the seventy North
American tree proxies, assuming the proxy values
to be TREND-LESS noise.
Surely you realized that the proxies combine the
signal components on which is superimposed the
noise? I find it hard to believe that you would
take data with obvious trends, would then directly
evaluate ACFs without removing the trends, and
then finally assume you had obtained results for
the proxy specific noise!
You will notice that the M&M inputs purport to show strong persistence out to lag-times of 350 years or
beyond. Your report makes no mention of this quite
improper M&M procedure used to obtain their ACFs.
Neither do you provide any specification data for
your own results that you contend confirm the M&M
results.
Relative to your Figure 4.4 you state “One of the most
compelling illustrations that M&M have produced is created by
feeding red noise (AR(1) with parameter = .2 into
the MBH algorithm”.
In fact they used and needed the extraordinarily
high persistances contained in the attatched
figure to obtain their `compelling’ results
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In other words, if you assume that Mann’s “hockey stick” was due to signal, rather than noise, and on the basis of that assumption you bias the frequency spectrum of the pseudo-random noise to filter out the low-frequencies in the data which you assume were really signal rather than noise, then you won’t get M&M’s result.
Don’t you see what’s wrong with that, caerbannog666? Your rationale for using a noise frequency spectrum which is different from that measured in the data is that you’ve assumed the result which you’re supposedly trying to test for.
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In other words, if you assume that Mann’s “hockey stick” was due to signal, rather than noise, and on the basis of that assumption you bias the frequency spectrum of the pseudo-random noise to filter out the low-frequencies in the data which you assume were really signal rather than noise, then you won’t get M&M’s result.
Given a matrix of tree-ring time-series (one column per time-series), there is a very straightforward way to test whether or not the “hockey stick PC” contains a genuine signal or is just a random noise artifact. And it requires no assumptions about the signal vs. noise frequency spectra.
You simply compute the inner-product of the hockey-stick PC with each of the columns in the tree-ring data matrix. If you have generated “noise matrices” that also produce leading “hockey-stick” PC’s, you do the same with those matrices.
It’s a very straightforward and simple test that McIntyre/Wegman neglected to perform.
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…
You simply compute the inner-product of the hockey-stick PC with each of the columns in the tree-ring data matrix.
…
Minor addendum to above:
In the case where Mann’s short-centered SVD procedure is used, there is one minor additional thing to do — recenter (shift) the tree-ring time-series so that they are zero-mean over their entire lengths. Then you can go ahead and compute inner-products as usual.
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That won’t differentiate between statistically significant signal and simple noise.
Loading...
That won’t differentiate between statistically significant signal and simple noise.
Burton clearly it unclear on the concept here. A signal would be defined as something common to most or all of the tree-ring time-series in your data-set.
The inner-product operation is basically a cross-correlation. A cross-correlation of two vectors basically tells you how much the two vectors have in common.
When you compute the inner-product of a “hockey stick” PC with one of the tree-ring time-series (column vectors) in your tree-ring data-matrix, you are effectively calculating how much “hockey stick” there is in that tree-ring time-series vector.
A significant positive correlation value is an indication that there is likely a significant amount of “hockey stick” in that tree-ring time-series. (Larger correlation values indicate lots of “hockey stick”; smaller correlation values indicate less “hockey” stick. Correlation values statistically near 0 indicate little or no “hockey stick”. Negative values would indicate negative “hockey stick”.)
Now if you compute inner-products/correlations of your “hockey stick” PC against *all* of your tree-ring time-series (in the case of Mann’s North America data, 70 time-series), you can get an indication of how much “hockey stick” there is in each individual tree-ring time-series.
If your correlation values are small and randomly greater/less than 0 (i.e. about half greater than 0, half less than 0), you can conclude that your hockey-stick is a noise artifact — there is little/no “hockey stick” in your data-set.
If your correlation values are significantly positive for all your tree-ring time-series, you can safely conclude that the “hockey stick” really does represent a climate signal common to all tree-ring time-series in your data-set.
In this particular case, the probability of having all correlations positive if your hockey-stick is a noise artifact are 1/2^70 (a *very* small number).
(For “weak signal” cases though, this may be a tough call.)
For strong-signal cases (as with Mann’s tree-ring data), it’s not that difficult a call. (BTW, Mann’s published eigenvalue magnitudes point to a “strong signal data-set).
This is a slam-dunk easy test to perform; adding it to existing tree-ring processing software would involve adding only a very few lines of new code.
Wegman/McIntyre should have performed this test and published a direct comparison of their tree-ring data vs. their “random noise” results. The fact that they haven’t (years after being requested to do so) should tell your something.
Professionals of all strips who make an honest effort to learn about topics outside of their specialties, who are willing to submit their findings to professional scrutiny, and who learn from / acknowledge errors that they may make while climbing the “outside their specialties” learning curve, can all earn the right to have their opinions considered trustworthy.
But that trust has to be *earned*. Launching attacks on scientists based on the results of undergraduate blunders is not the way to earn that trust.
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That’s “Professionals of all *stripes*”
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Good answer.
Unfortunately, Mann fails that test. He’s been unwilling to submit his statistical findings to professional statisticians’ scrutiny, and he refuses to learn from / acknowledge the errors he made while working outside his specialty. You can read about it here: http://a-sceptical-mind.com/the-rise-and-fall-of-the-hockey-stick
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Yet ANOTHER patented daveburton link to a denialist website, and if you look at the list of “useful sites” there, you will find only denialists and skeptics—-the ever-shrinking circular firing squad. Check out the “articles” list—you will find one titled “the arctic is not melting” that shows a series of temperature graphs but NEVER mentions the exponential decline in arctic sea ice.
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The Mann has failed to publish the code meme is an oft repeated lie. It’s easy to debunk. It’s on Wikipedia. Dave is not even trying to hide bias or delusion anymore. He only listens to sources that feed him fairy tales he wants to believe. Delusional.
“Mann indicated in testimony that the methods and data had been available since May 2000, including the necessary algorithms, in full accordance with National Science Foundation requirements, but NSF policy was that computer codes were proprietary and not subject to disclosure. Despite this, the full code used for MBH98 had been made public.” http://en.wikipedia.org/wiki/Wegman_Report
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Caerbon – apparently DB is too weak minded to realize that your field of study requires a high degree of concentration in probability and statistics. Not surprised. DB has an inflated view of his own qualifications. Dunning – Kruger.
Dave is just lying, but he has swallowed his own lies for so long, he does not know the difference between his own wishful thinking and the truth. The Mann paper has several authors, not one, and it’s methods have been critiqued by many. That would be impossible if the appear withheld that information. But he makes his bold claim without qualification, reservation, or humility. somehow, despite the fact that the hockey stick graph has been reproduced independently more than a dozen times, even by Muller, a misguided detractor, Dave is on about Mann. Overlooking the forest for the trees? Dave somehow thinks that by attacking Mann, or Gore, or whatever his wishful thinking requires, GW will go away, then he can sell his beachfront real estate. Because those red flood lines will be in the ocean where he wants them. In a massive concern for his underwater investments, he spends hours scouring the internet for empty minded troll drivel echoing through the denier sphere to counter peer reviewed literature. Frustrated by the lack of scientists crazy enough to support whacko denier theories, he has donned a tin foil miter and exalted himself with an imaginary scientific ability. This has allowed him to imagine sea level only rising in the center of the ocean, allowing his beachfront view status quo. Now that’s a dedicated real estate person. If my home were submerging or even submarine, he would be the first person I would call. Of course, I would probably just find the local Heartland list and Fox News listeners…..he looks genuinely sad in his youtube video pleading the nc-20 line…
You should post that Dave Burton youtube video every time he posts. Its pathetic. One look into his eyes and that plaintive voice pleading… It tells more about why his mind is contorted and why it is a waste of time replying to him. Before that, all you can do is scratch your head and respond to the silliness with logic. Afterwords… I feel pity, but not in a completely nice way. He is incapable of reason once this subject is broached. It has to do with psychology, not background or intellect. The lizard brain destroys reason.
“The lizard brain destroys reason”. Actually, in Dave’s case, since he is a proud “conservative”, it drives what substitutes for “reason”. Read The Republican Brain by Mooney for a rundown on how the amygdala governs conservative “thinking”.
You see what I mean? He says there are no legal restrictions, but he can’t unload his questionable real estate when people are saying it will be underwater soon. Gosh. We should just declare the water will never rise. Oh wait. NC did that. Its not enough that the government should be cowed into submission allowing him to sell underwater assets, he wants everyone else to collude in his swindle. Thats why he’s here begging us to stop saying sea level rise. Nerve. And never say the word acceleration. Oops. Now he won’t calm down for days.
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You should post that Dave Burton youtube video every time he posts. Its pathetic.
I missed the ref’ to that.
Is it this one:
David Burton offers one reason for alarmist predictions about N.C.
Just watched it again. Was a bit more aware this time of Dave’s complaining about how he and his ilk are “bullied” by those HE would attempt to bully with misinformation and lies. Pathetic and lizard brain, indeed!
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PS Forgot to say that we need to get his real estate agent wife to take a bit more care dressing him before she sends him out the door—that outfit doesn’t quite make it.
And he was a bit coherent in the beginning of his talk—he DOES at least recognize that people won’t buy land that is under water. That is why he and Droz and NC-20 worked so hard to get the NC legislature to outlaw sea level rise!
I’m sure The Who anticipated trolls. Also add the lyrics: “Don’t try to dig what we all s-s-s-say. We’re just tryin’ to start a big s-s-s-sensation” (with apologies to Pete and the boys’ “Talkin’ ’bout My Generation)
http://www.mnn.com/sites/default/files/JamesHansenNASA_main_0124.jpg
What’s your point, troll? Hansen has blue eyes? So what, so do I and a lot of other people. Your “humor” escapes me.
OTOH, we all know that daveburton’s eyes are brown because he is a walking demonstration of the old saw about “His eyes are brown because he’s so full of ****”.
(Or is my saying that one of those “vicious” things that Dave alleges others have done but won’t give details about, even when asked repeatedly to do so?)
Here you go, old guy, as requested.
As Coach Orem would ask us boys, “Who started this fight, Morano or Mann?
Stalin had brown eyes, Pol Pot had black eyes…
What was your point, exactly?
From the “How it’s Done. Mann v. Morano” thread below
Burton said,
One of the questions at issue is whether or not there really was a hockey-stick signal in the tree rings, at all.
Gee, why didn’t McIntyre/Wegman think about answering that question *before* they went running around making claims about “random noise” hockey sticks? Why didn’t McIntyre think about answering that question *before* he testified in front of Congress about Mann’s supposed “random noise hockey-sticks”? Why didn’t Wegman think about that *before* he submitted his report to Congress?
And why didn’t anyone else in the denier community think about investigating that question?
The above question is a question that should have been answered *before* McIntyre/Wegman blindly used the tree-ring data as a noise template. And it should have been answered *before* they told Congress that Mann’s method makes hockey sticks out of random noise.
The very first thing any *competent* analyst would do before said analyst used tree-ring data as a noise model would be to *look at the data* to determine whether there is low-frequency “hockey stick” climate signal that needs to filtered out.
No competent analyst would blindly assume that there’s no signal in the data
And yes, even a crude non-area-weighted average of the data will reveal an underlying “hockey-stick” pattern — it’s noisy, but it’s there. That pattern is clearly a very low frequency signal with a correlation time that is significant relative to the data length. It is quite visible, and very obviously must be filtered out.
Long correlation times relative to the length of your data will greatly increase the likelihood of producing spurious (false) trends, for reasons that are explained in any Time Series Analysis 101 course.
Taking raw, unfiltered tree-ring chronologies and blindly using them as a noise model without first looking to see what is actually in them is a colossal blunder.
Folks, this whole “Mann’s method makes hockey sticks from random noise” business is a perfect example of ideologically-driven incompetence. Incompetence that is rife in the denier community.
caerbannog666, there’s a question awaiting you over there.
caerbannog666 wrote, “Taking raw, unfiltered tree-ring chronologies and blindly using them as a noise model…”
I think you must at least suspect that such a mistake actually was not made by three highly credentialed PhD statisticians:
The Bernard J. Dunn Professor of Statistics at George Mason University, a Fellow of the American Statistical Association, past chair of the U.S. National Research Council’s Committee on Applied and Theoretical Statistics, and former president of the International Association for Statistical Computing.
And,
The Noah Harding Professor of Statistics, and Chair of the Department of Statistics at Rice University.
And,
A Research Professor from the National Institutes of Health at George Mason University, a Visiting Fellow at the Isaac Newton Institute for Mathematical Sciences at the University of Cambridge in England, and Co-Director of the Center for Computational Data Sciences in the College of Science at George Mason U.
What are your statistics creds, caerbannog666?
And have you actually read the 91-page Report of which you are so critical?
Here’s a link to the R-code used by Wegman/McIntyre to generate synthetic random noise modeled after the characteristics of tree-ring noise:
http://onlinelibrary.wiley.com/store/10.1029/2004GL021750/asset/supinfo/grl19230-sup-0005-script.final.txt?v=1&s=21393553c15a389b824130b356f572ae506a6420
If you are certain that those statisticians did not make the mistake that I described, then please point out the lines in the above R script where they test the tree-ring data for the presence of a low-frequency climate signal (aka “hockey stick”) and then remove that signal from the tree-ring data before they use the tree-ring data as a model for their synthetic random noise.
(Unless the low-frequency signal is removed, the resulting synthetic noise model will be useless for generating true “noise-only” results.)
To make the code easier to navigate, I suggest copy/pasting it into an “R-aware” editor and using that editor’s syntactic highlighting and auto-indentation features to make the code easier to read through.
You seem to have overlooked my questions, caerbannog666.
What are your statistics credentials?
And have you actually read the 91-page Report of which you are so critical?
Two engineering degrees from the University of California: a BS in engineering, and an MSEE with an emphasis on communication-theory/stochastic-processes/detection-theory.
As for the Wegman Report — I’ve read the portions relevant to the material that I’ve been critical of here.
So you have no formal statistics creds, but with your background you should be able to learn such topics, with sufficient work.
It is surprising to me that someone with a background so very similar to my own does not “get it.” Some folks here just don’t have the “tools” to understand the topics, but you should. So why don’t you?
For instance, most engineers would look at Muller’s criticism of Mann’s fraud and understand it, and be properly outraged at Mann’s fraud. But you aren’t. Most engineers would look at these graphs of sea level and immediately recognize the disconnect between the data and the alarmists’ claims. But you don’t.
You’re a lot like Peter. Apart from his excellent taste in music, he’s wrong about almost everything. Climate alarmists seem to filter out any information that conflicts with their prejudices, no matter how compelling, and latch onto even the flimsiest of evidence that confirms those prejudices.
It is surprising to me that Dave actually thinks caerbannog666 has “a background so very similar to his”. And he then chastises him for “not getting it”? And Peter “is wrong about almost everything”?. And “Climate alarmists?”
I have said it before, but it bears repeating. Dave is shameless. And a distraction (AND a poison to the Crock community). If Dave had worked for me back in the day, he would be collecting unemployment benefits long ago.
For the lurkers:
This is an email from Stanford Professor Emeritus David Ritson to Ed Wegman regarding the “hockey sticks from noise” business (linky http://www.meteo.psu.edu/holocene/public_html/house06/RitsonWegmanRequests.pdf)
It’s reformatted a bit and emphasis has been added (if I didn’t mess up the tags).
Note that it confirms exactly what I have been saying here — that the McIntyre/Wegman noise model was badly contaminated with “hockey stick” signal statistics.
Dear Dr Wegman and colleagues,
I am forwarding below an e-mail I sent you and
your colleagues requesting essential, but missing,
basic, information relative to your report to
Congress.
To facilitate a reply I attach the
Auto-Correlation Function used by the M&M to
generate their persistent red noise simulations
for their figures shown by you in your Section 4
(this was kindly provided me by M&M on Nov 6
2004).
The black values are the ones actually used by
M&M. They derive directly from the seventy North
American tree proxies, assuming the proxy values
to be TREND-LESS noise.
Surely you realized that the proxies combine the
signal components on which is superimposed the
noise? I find it hard to believe that you would
take data with obvious trends, would then directly
evaluate ACFs without removing the trends, and
then finally assume you had obtained results for
the proxy specific noise!
You will notice that the M&M inputs purport to show
strong persistence out to lag-times of 350 years or
beyond. Your report makes no mention of this quite
improper M&M procedure used to obtain their ACFs.
Neither do you provide any specification data for
your own results that you contend confirm the M&M
results.
Relative to your Figure 4.4 you state “One of the most
compelling illustrations that M&M have produced is created by
feeding red noise (AR(1) with parameter = .2 into
the MBH algorithm”.
In fact they used and needed the extraordinarily
high persistances contained in the attatched
figure to obtain their `compelling’ results
In other words, if you assume that Mann’s “hockey stick” was due to signal, rather than noise, and on the basis of that assumption you bias the frequency spectrum of the pseudo-random noise to filter out the low-frequencies in the data which you assume were really signal rather than noise, then you won’t get M&M’s result.
Don’t you see what’s wrong with that, caerbannog666? Your rationale for using a noise frequency spectrum which is different from that measured in the data is that you’ve assumed the result which you’re supposedly trying to test for.
In other words, if you assume that Mann’s “hockey stick” was due to signal, rather than noise, and on the basis of that assumption you bias the frequency spectrum of the pseudo-random noise to filter out the low-frequencies in the data which you assume were really signal rather than noise, then you won’t get M&M’s result.
Given a matrix of tree-ring time-series (one column per time-series), there is a very straightforward way to test whether or not the “hockey stick PC” contains a genuine signal or is just a random noise artifact. And it requires no assumptions about the signal vs. noise frequency spectra.
You simply compute the inner-product of the hockey-stick PC with each of the columns in the tree-ring data matrix. If you have generated “noise matrices” that also produce leading “hockey-stick” PC’s, you do the same with those matrices.
It’s a very straightforward and simple test that McIntyre/Wegman neglected to perform.
…
You simply compute the inner-product of the hockey-stick PC with each of the columns in the tree-ring data matrix.
…
Minor addendum to above:
In the case where Mann’s short-centered SVD procedure is used, there is one minor additional thing to do — recenter (shift) the tree-ring time-series so that they are zero-mean over their entire lengths. Then you can go ahead and compute inner-products as usual.
That won’t differentiate between statistically significant signal and simple noise.
That won’t differentiate between statistically significant signal and simple noise.
Burton clearly it unclear on the concept here. A signal would be defined as something common to most or all of the tree-ring time-series in your data-set.
The inner-product operation is basically a cross-correlation. A cross-correlation of two vectors basically tells you how much the two vectors have in common.
When you compute the inner-product of a “hockey stick” PC with one of the tree-ring time-series (column vectors) in your tree-ring data-matrix, you are effectively calculating how much “hockey stick” there is in that tree-ring time-series vector.
A significant positive correlation value is an indication that there is likely a significant amount of “hockey stick” in that tree-ring time-series. (Larger correlation values indicate lots of “hockey stick”; smaller correlation values indicate less “hockey” stick. Correlation values statistically near 0 indicate little or no “hockey stick”. Negative values would indicate negative “hockey stick”.)
Now if you compute inner-products/correlations of your “hockey stick” PC against *all* of your tree-ring time-series (in the case of Mann’s North America data, 70 time-series), you can get an indication of how much “hockey stick” there is in each individual tree-ring time-series.
If your correlation values are small and randomly greater/less than 0 (i.e. about half greater than 0, half less than 0), you can conclude that your hockey-stick is a noise artifact — there is little/no “hockey stick” in your data-set.
If your correlation values are significantly positive for all your tree-ring time-series, you can safely conclude that the “hockey stick” really does represent a climate signal common to all tree-ring time-series in your data-set.
In this particular case, the probability of having all correlations positive if your hockey-stick is a noise artifact are 1/2^70 (a *very* small number).
(For “weak signal” cases though, this may be a tough call.)
For strong-signal cases (as with Mann’s tree-ring data), it’s not that difficult a call. (BTW, Mann’s published eigenvalue magnitudes point to a “strong signal data-set).
This is a slam-dunk easy test to perform; adding it to existing tree-ring processing software would involve adding only a very few lines of new code.
Wegman/McIntyre should have performed this test and published a direct comparison of their tree-ring data vs. their “random noise” results. The fact that they haven’t (years after being requested to do so) should tell your something.
And this question, too:
http://climatecrocks.com/2014/02/01/how-its-done-mann-v-morano-on-bbc/comment-page-1/#comment-46671
Professionals of all strips who make an honest effort to learn about topics outside of their specialties, who are willing to submit their findings to professional scrutiny, and who learn from / acknowledge errors that they may make while climbing the “outside their specialties” learning curve, can all earn the right to have their opinions considered trustworthy.
But that trust has to be *earned*. Launching attacks on scientists based on the results of undergraduate blunders is not the way to earn that trust.
That’s “Professionals of all *stripes*”
Good answer.
Unfortunately, Mann fails that test. He’s been unwilling to submit his statistical findings to professional statisticians’ scrutiny, and he refuses to learn from / acknowledge the errors he made while working outside his specialty. You can read about it here:
http://a-sceptical-mind.com/the-rise-and-fall-of-the-hockey-stick
Yet ANOTHER patented daveburton link to a denialist website, and if you look at the list of “useful sites” there, you will find only denialists and skeptics—-the ever-shrinking circular firing squad. Check out the “articles” list—you will find one titled “the arctic is not melting” that shows a series of temperature graphs but NEVER mentions the exponential decline in arctic sea ice.
The Mann has failed to publish the code meme is an oft repeated lie. It’s easy to debunk. It’s on Wikipedia. Dave is not even trying to hide bias or delusion anymore. He only listens to sources that feed him fairy tales he wants to believe. Delusional.
“Mann indicated in testimony that the methods and data had been available since May 2000, including the necessary algorithms, in full accordance with National Science Foundation requirements, but NSF policy was that computer codes were proprietary and not subject to disclosure. Despite this, the full code used for MBH98 had been made public.”
http://en.wikipedia.org/wiki/Wegman_Report
Caerbon – apparently DB is too weak minded to realize that your field of study requires a high degree of concentration in probability and statistics. Not surprised. DB has an inflated view of his own qualifications. Dunning – Kruger.
Dave is just lying, but he has swallowed his own lies for so long, he does not know the difference between his own wishful thinking and the truth. The Mann paper has several authors, not one, and it’s methods have been critiqued by many. That would be impossible if the appear withheld that information. But he makes his bold claim without qualification, reservation, or humility. somehow, despite the fact that the hockey stick graph has been reproduced independently more than a dozen times, even by Muller, a misguided detractor, Dave is on about Mann. Overlooking the forest for the trees? Dave somehow thinks that by attacking Mann, or Gore, or whatever his wishful thinking requires, GW will go away, then he can sell his beachfront real estate. Because those red flood lines will be in the ocean where he wants them. In a massive concern for his underwater investments, he spends hours scouring the internet for empty minded troll drivel echoing through the denier sphere to counter peer reviewed literature. Frustrated by the lack of scientists crazy enough to support whacko denier theories, he has donned a tin foil miter and exalted himself with an imaginary scientific ability. This has allowed him to imagine sea level only rising in the center of the ocean, allowing his beachfront view status quo. Now that’s a dedicated real estate person. If my home were submerging or even submarine, he would be the first person I would call. Of course, I would probably just find the local Heartland list and Fox News listeners…..he looks genuinely sad in his youtube video pleading the nc-20 line…
One of your better efforts at analyzing-interpreting-explaining-understanding the strange phenomenon that is Dave. It’s not an easy task. Good work!
You should post that Dave Burton youtube video every time he posts. Its pathetic. One look into his eyes and that plaintive voice pleading… It tells more about why his mind is contorted and why it is a waste of time replying to him. Before that, all you can do is scratch your head and respond to the silliness with logic. Afterwords… I feel pity, but not in a completely nice way. He is incapable of reason once this subject is broached. It has to do with psychology, not background or intellect. The lizard brain destroys reason.
“The lizard brain destroys reason”. Actually, in Dave’s case, since he is a proud “conservative”, it drives what substitutes for “reason”. Read The Republican Brain by Mooney for a rundown on how the amygdala governs conservative “thinking”.
You see what I mean? He says there are no legal restrictions, but he can’t unload his questionable real estate when people are saying it will be underwater soon. Gosh. We should just declare the water will never rise. Oh wait. NC did that. Its not enough that the government should be cowed into submission allowing him to sell underwater assets, he wants everyone else to collude in his swindle. Thats why he’s here begging us to stop saying sea level rise. Nerve. And never say the word acceleration. Oops. Now he won’t calm down for days.
You should post that Dave Burton youtube video every time he posts. Its pathetic.
I missed the ref’ to that.
Is it this one:
David Burton offers one reason for alarmist predictions about N.C.
http://www.youtube.com/watch?v=vxLHCXah-6o
?
Coherent presentation – 0 out of 10
‘Ideological investment’ – his words – he has it in spades.
Just watched it again. Was a bit more aware this time of Dave’s complaining about how he and his ilk are “bullied” by those HE would attempt to bully with misinformation and lies. Pathetic and lizard brain, indeed!
PS Forgot to say that we need to get his real estate agent wife to take a bit more care dressing him before she sends him out the door—that outfit doesn’t quite make it.
And he was a bit coherent in the beginning of his talk—he DOES at least recognize that people won’t buy land that is under water. That is why he and Droz and NC-20 worked so hard to get the NC legislature to outlaw sea level rise!