The AR2 term p=0.20

The MA2 term p=0.03

with AR4 p=0.005 and MA4 0.10

I remember from a previous discussion on ‘spurious regression’ how the inclusion of an MA term altered the perspective and wondered if it might also be the case here. A ten period ‘forecast’ plot based on the the full ARMA is qualitatively very different from the one generated from an AR2 analysis.

-My grotty point-grabbing might be contributing to all this: my points have a trend (0.04 degrees in 100 years) and add up to 0.13 ]]>

However, this is probably the most important paragraph:

Although we focus on presenting a methodology for the uncertainty analysis, it is worth to mention that the reconstruction is only robust under the given assumptions. However, there is a possibility of violations of those assumptions. For example, the increase of CO2 may accelerate the growth of trees (e.g. MBH99), so that makes the recent relationship between tree rings and temperature differ from the past. If this is true, it will break the important statistical assumption of a stationary relationship between temperature and proxies. In addition, because the proxy records end in 1980, the warm decades since then cannot be reconstructed. Hence, based on the stationarity assumption, we use the instrumental data for this period.

In other words, these error estimates are only good when the proxies are linear and stationary. Has this ever been shown for the tree rings that they use in this paper?

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