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Apr 2, 2010 16:16:13 GMT
Post by hunter on Apr 2, 2010 16:16:13 GMT
icefisher, No big deal. VS seems to be having a tough time of it, currently. I have a question posted at Lucia's and am hoping for a clear answer.
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Puzzle
Apr 3, 2010 22:32:57 GMT
Post by socold on Apr 3, 2010 22:32:57 GMT
Gee Icefisher there is plenty of evidence for a trend These deluded economonists were trying to determine whether temperature was instead governed by some sort of weird stochastic based variation as though the propensity for things to warm up might be determined by the same rules as those that tell us the amount of money old people hide under the mattress. It's hard to put into words, but there does seem to be a mistake with applying statistics to data but not factoring in the physical constraints of what the data represents. There's a good analogy here with the link between calorie intake and weight gain, which makes it clearer that there is indeed a mistake with the pure statistical approach, even though I still can't explain precisely what the error is. ourchangingclimate.wordpress.com/2010/04/01/a-rooty-solution-to-my-weight-gain-problem/
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Puzzle
Apr 4, 2010 1:55:20 GMT
Post by icefisher on Apr 4, 2010 1:55:20 GMT
Gee Icefisher there is plenty of evidence for a trend These deluded economonists were trying to determine whether temperature was instead governed by some sort of weird stochastic based variation as though the propensity for things to warm up might be determined by the same rules as those that tell us the amount of money old people hide under the mattress. It's hard to put into words, but there does seem to be a mistake with applying statistics to data but not factoring in the physical constraints of what the data represents. There's a good analogy here with the link between calorie intake and weight gain, which makes it clearer that there is indeed a mistake with the pure statistical approach, even though I still can't explain precisely what the error is. Probably because the error is in your interpretation of what is being implied here. What is being said is one cannot claim observational evidence of AGW nor can one scientifically justify parameterizing a model using temperature observations (either directly or undirectly as in feedback assumptions built and parameterized on observational data.) The calorie/exercise weight gain/loss example is better understood and does not related to this situation. . . .though there are elements in it. Here is an example of the fallacy that can be generated from applying the wrong statistics in the presence of a unit root. If it rains the sidewalk will get wet. The sidewalk is wet. Therefore; it rained. The problem is when you apply the right statistics no correlation is found. That does not mean there is no AGW, it just means you cannot verify scientifically from observations.
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Apr 4, 2010 3:10:45 GMT
Post by socold on Apr 4, 2010 3:10:45 GMT
What do you mean "is better understood"? How does understanding of the phenomenon affect the application of VS's statistical method? VS didn't mention anything about factoring in understanding about the physics of temperature. He seemed to just apply a pure statistical method to data without needing to know the nature of what that data was.
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Apr 4, 2010 4:50:40 GMT
Post by icefisher on Apr 4, 2010 4:50:40 GMT
What do you mean "is better understood"? How does understanding of the phenomenon affect the application of VS's statistical method? VS didn't mention anything about factoring in understanding about the physics of temperature. He seemed to just apply a pure statistical method to data without needing to know the nature of what that data was. What I was saying is we understand the calorie to weight issue much better. That has nothing to do with statistics though. Let me try to explain. More than likely using the correct statistical test for the weight calorie example would return a correlation while AGW did not. I am guessing but the reason would likely be found in this statement: "As you can see from this graph, I’ve been on quite a few diets. But often, as soon as I had loosed a few pounds, they came back when I lost my appetite in carrots and hunted down the chocolate isle again. In the nineties, I sported quite a bit, which prevented my weight from increasing too much. I’ve stopped since; it just makes me tired." LOL! We have the same AGW graph but we don't have the same physics. We have the same shape graph for AGW but we have not been removing and reinserting CO2 into the atmosphere to follow the track of the graph like the guy has been doing with his sports and carrot diet. In other words if you use a cointegration statistics method and providing the guy has a few reliable date records of when he dumped the carrots and chased the chocolate to go along with his time/weight graph a correlation would probably be found. Thats why when VS applied the correct test, temperature correlated to sun activity (as we have also seen with the NOAA graph) and CO2 does not. Ultimately what VS is telling us is exactly what Akasofu told us. Just that VS is doing it using statistics. Akasofu did it verbally with intuition born of his extensive experience. I see a lot of people challenging VS but I don't see anybody really on target. Most are talking about irrelevant stuff. Ultimately one fellow seemed to corrall it in VS favor, namely it gets down the parameterization of models using observations to estimate feedback and such. There is no scientific basis for the parameterizations. Early in my career I did logic and math checks on big models. The results of these economic models were entirely dependent upon parameterizations of such assumptions like changing interest rates, inflation, tax rates, and such. The classic economic model bubble is the assumption that up trends in those items will continue forever. In the AGW case, its the assumption that CO2 is the only way the system changes. Its like building a model that assumes interest rates are going to keep climbing and not even have anything in the model about inflation. You do this stuff long enough and intuition alone raises red flags. I can't argue the fine points on this issue or test any of VS's runs all I can do is vouch for the issue and say bully somebody has found a mathematical method of dealing with the issue.
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Puzzle
Apr 4, 2010 12:49:48 GMT
Post by socold on Apr 4, 2010 12:49:48 GMT
You say "We have the same AGW graph but we don't have the same physics". VS didn't factor in anything to do with physics, he used a pure statistical method and claimed it meant something. In such a way there's no way for his method to distinguish the co2-temperature case from the calorie intake-weight case. Therefore his method will show the same conclusion for both. So whatever he found wrt co2-temperature would apply to the caloire inteake-weight case too.
If the physical difference between the two does matter and has to be taken into account, then VS's approach which didn't take anything like that into account is invalid.
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Puzzle
Apr 4, 2010 16:43:56 GMT
Post by trbixler on Apr 4, 2010 16:43:56 GMT
socold post over at vs site and see how well your argument stands up. Tell us how it all comes out. You say "We have the same AGW graph but we don't have the same physics". VS didn't factor in anything to do with physics, he used a pure statistical method and claimed it meant something. In such a way there's no way for his method to distinguish the co2-temperature case from the calorie intake-weight case. Therefore his method will show the same conclusion for both. So whatever he found wrt co2-temperature would apply to the caloire inteake-weight case too. If the physical difference between the two does matter and has to be taken into account, then VS's approach which didn't take anything like that into account is invalid.
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Apr 4, 2010 17:11:17 GMT
Post by icefisher on Apr 4, 2010 17:11:17 GMT
You say "We have the same AGW graph but we don't have the same physics". VS didn't factor in anything to do with physics, he used a pure statistical method and claimed it meant something. In such a way there's no way for his method to distinguish the co2-temperature case from the calorie intake-weight case. Therefore his method will show the same conclusion for both. So whatever he found wrt co2-temperature would apply to the caloire inteake-weight case too. If the physical difference between the two does matter and has to be taken into account, then VS's approach which didn't take anything like that into account is invalid. If you were Adam testing your newly minted weight/calorie theory through a single observation of Eve over a period of time you would need to be disciplined in your approach. Of course that is not how the weight/calorie connection was originally established. It was established through experimentation not statistics. Likewise some of the physics in the AGW theory can be tested by experimentation and that which cannot be tested by experimentation needs to be established via statistical analysis of observations. You are wrong to conclude the statistics will find the same results for both cases. What is found is both cases should be rigorous in their application of statistics because of the existence of a unit root in the data. All you are arguing is you should not be careful in the use of statistics for global warming because its not necessary to carefully run rigorous statistical tests to conclude that you will get fat if you switch from carrots to chocolate and stop exercising. Sorry Socold I am not buying that. Seems to be just more malarkey from you.
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Puzzle
Apr 4, 2010 23:11:24 GMT
Post by socold on Apr 4, 2010 23:11:24 GMT
VS's response to the presentation of the calories intake/weight gain example using the same data was: VS: "hahaha… this blog entry is funny.. "Riiiight. If he had a point why didn't he make it? What I am arguing is that whatever VS claimed about the co2 vs temperature record because it had a "unit root", must also apply to the calories intake/weight gain example - because it too has a "unit root". So what exactly is VS claiming a unit root proves in both cases? I am arguing nothing more nothing less. If you all understand what VS is saying, which I actually doubt, then you could just answer my question.
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Puzzle
Apr 5, 2010 2:00:38 GMT
Post by icefisher on Apr 5, 2010 2:00:38 GMT
VS's response to the presentation of the calories intake/weight gain example using the same data was: VS: "hahaha… this blog entry is funny.. "Riiiight. If he had a point why didn't he make it? What I am arguing is that whatever VS claimed about the co2 vs temperature record because it had a "unit root", must also apply to the calories intake/weight gain example - because it too has a "unit root". So what exactly is VS claiming a unit root proves in both cases? I am arguing nothing more nothing less. If you all understand what VS is saying, which I actually doubt, then you could just answer my question. You should be more careful Socold. Intentionally excluding information is the earmark of your buddies in the AGW community. It reflects poorly on your integrity. On the same page you have picked two items there is also this item: "VS Says: April 3, 2010 at 21:11 “The fact that your weight gain has a unit root doesn’t exclude the possibility of causally attributing (some or all) of your weight gain to calories, genes, etc., and your weight loss to diets and exercise. It just means that, after you’ve gathered all the data points on forcings and the movement of your weight (up and down through time), you have to apply whatever statistical method is consistent with the presence of the unit root (e.g. co-integration).” I think you clarified it pretty well Best, VS" Seems you are playing word games. You asked what is established by the presence of a unit root. What a series of data that has a unit root exhibits is different from when you have a stationary trend, deviations from a stationary trend tend to show strong returns to the trend. When deviations lollygag away from the trend for extended periods of time its suggestive that returns to the trend only occur by chance if they return at all. When you have that situation of "non-stationarity", you should apply a statistical method that is compatible with the presence of a unit root to test for correlation because if you do not you might be otherwise using good statistics tests like "ordinary least squares" and produce results with alleged high R 2 and T values that is nothing but garbage. What this means is a significant increase in the burden of proof and explains why this is being vigorously opposed but as VS says the unit root is a result of his calculations and everybody is protesting for all sorts of reasons but nobody is producing calculations to show he is wrong. That is no doubt because that test has already been applied to global warming years ago, a unit root was found, and then the test was rejected without argument instead of the AGW hypothesis. It was discovered to be an "inconvenient" test.
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Apr 5, 2010 2:20:32 GMT
Post by sigurdur on Apr 5, 2010 2:20:32 GMT
Ok......who is VS?
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Apr 5, 2010 3:25:53 GMT
Post by socold on Apr 5, 2010 3:25:53 GMT
VS's response to the presentation of the calories intake/weight gain example using the same data was: VS: "hahaha… this blog entry is funny.. "Riiiight. If he had a point why didn't he make it? What I am arguing is that whatever VS claimed about the co2 vs temperature record because it had a "unit root", must also apply to the calories intake/weight gain example - because it too has a "unit root". So what exactly is VS claiming a unit root proves in both cases? I am arguing nothing more nothing less. If you all understand what VS is saying, which I actually doubt, then you could just answer my question. You should be more careful Socold. Intentionally excluding information is the earmark of your buddies in the AGW community. It reflects poorly on your integrity. It's the earmark of the skeptic community. Like telling people that humans only emit 3% of co2 emissions without telling them the context. I didn't exclude it. I pointed out that VS's response to the post was "hahaha… this blog entry is funny.. "If we rewrite the start of the post someone else wrote for him, in terms of temperature and co2 we get: "The fact that global temperature has a unit root doesn't exclude the possibility of causally attributing some or all of the temperature rise to greenhouse gas forcing. It just means that, after you’ve gathered all the data points on forcings and the movement of temperature (up and down through time), you have to apply whatever statistical method is consistent with the presence of the unit root (e.g. co-integration)" Why do you have to apply any statistical method? The causative link between co2 and temperature is not based on statistics. Then it also means there must be a significant increase in the burden of proof that excess calories cause weight gain...
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Apr 5, 2010 3:47:32 GMT
Post by sigurdur on Apr 5, 2010 3:47:32 GMT
SoCold wrote: "Why do you have to apply any statistical method? The causative link between co2 and temperature is not based on statistics."
Yes it is SoCold. Or are you changing the meaning of stats?
And the causative link between co2 and temp is murky at best.
Yes, in a slab it appears to cause. In the real world of climate, that causative link is not prevelant, and upon examination fails.
The hot spot isn't there. The stratosphere is not cooling. There are so many things that were predicted by the GCM's that are not coming to pass that it shows how they have failed.
The very sad thing is that the government funded researchers are not looking for the reasons that there is failure. They are too busy defending themselves so their funding doesn't dry up. If they were employeed in the private sector, they would have been canned long ago for lack of insight.
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Apr 5, 2010 3:54:22 GMT
Post by socold on Apr 5, 2010 3:54:22 GMT
The causative link between co2 and temperature is based on physics. It isn't based on looking at the mauna loa co2 curve and looking at the GISTEMP temperature curve and applying some correlation test.
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Apr 5, 2010 5:52:38 GMT
Post by icefisher on Apr 5, 2010 5:52:38 GMT
"The fact that global temperature has a unit root doesn't exclude the possibility of causally attributing some or all of the temperature rise to greenhouse gas forcing. It just means that, after you’ve gathered all the data points on forcings and the movement of temperature (up and down through time), you have to apply whatever statistical method is consistent with the presence of the unit root (e.g. co-integration)" Why do you have to apply any statistical method? The causative link between co2 and temperature is not based on statistics. I agree with you that there is no link between observations and CO2 and temperature. But you might provide some links to the physics papers that links global warming to CO2 without observations over time. . . .I must have missed them. In case you have some trouble finding them perhaps you can peruse this 1944 paper that led to a Nobel Prize on how you might go about establishing a link between CO2 and global temperatures via observation. stevereads.com/papers_to_read/the_probability_approach_in_econometrics.pdfThen it also means there must be a significant increase in the burden of proof that excess calories cause weight gain... Yes it would, if and only if you intended to establish the link using one individuals weight history. But of course that is not how the link was established.
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