Is Ritson making the precise point that VS introduced autocorrelated noise, whereas the real data series do not show short term autocorrelated noise ? ❋ Unknown (2006)
Income is fairly persistent (autocorrelated) while civil wars are not, so taking all cross country information out of the mix is going to inflate the standard errors on the persistent variables (by reducing the variance of the independent variable). ❋ Unknown (2008)
I would remind commenter Forlornehope that climate data time series are highly autocorrelated, so that simple linear regression isn't really appropriate. ❋ Unknown (2008)
I take your point about autocorrelated data, however CUSUM, presumes neither normal distribution nor stability. ❋ Unknown (2008)
The trees correlate much better with regional temp averages e.g., the CRU gridded data because temp tends to be more spatially autocorrelated than ppt and the regional averages reduce the effects of individual station anomalies. ❋ Unknown (2007)
If the residuals are autocorrelated that is surely prima facie evidence that the relationship estimated has left out important variables. ❋ Unknown (2007)
Both of the time series are autocorrelated, so the term “spurious” comes to mind. ❋ Unknown (2007)
In general, what you really ought to do is start with a statistical model for the data y(t) as the sum of a smooth trend function m(t) selected from some probability space and zero-mean errors e(t) (which may be autocorrelated) and then work out what weights give you the best estimate of the trend function from the data – linear regression being a good starting point. ❋ Unknown (2007)
An econometrician looking at the residuals from such an enterprise would observe highly autocorrelated residuals and conclude that the process had been mis-specified or perhaps that some of the data was bad. ❋ Unknown (2007)
The climate data may not be consistent with these priors, and autocorrelated errors complicates analysis, but these issues are generally not insurmountable. ❋ Unknown (2007)
One is the autocorrelated nature of tree growth due to “physiological preconditioning” carryover effects – which we all agree on. ❋ Unknown (2007)
One explanation can be autocorrelated noise, but I have something else in my mind: ❋ Unknown (2007)
We still have all kinds of mushy issue analysis wirh repect to red noise is inadequate handling of autocorrelated signals the issue or would the complaints about bcp promotion in PCA exist even if there was a “sheep” signal in that strong rise, oh…and how the hell do rings exhibit year after year accumulation in a randowm walk manner which Steve posits. ❋ Unknown (2007)
They say that using one of the usual smoothing methods on autocorrelated data tends to under-smooth, and use climate data as a particular example. ❋ Unknown (2007)
For example, highly autocorrelated stationary processes may look very ‘trendy’. ❋ Unknown (2007)
You need to watch it if there are outliers from non-Gaussian heavy-tailed distributions, and a favourite topic of yours, I believe heavily autocorrelated errors like stationary ARMA processes. ❋ Unknown (2007)
Define residuals as r=p-T, where p is proxy-based reconstruction and T instrumental temperature, and observe that residuals are autocorrelated. ❋ Unknown (2007)
If the hurricane counts are autocorrelated, then they are not from an idd Poisson process, and the claim that the mean is constant is incorrect. richardT ❋ Unknown (2007)
[Jim]: "do you [wanna play] penis"
Jake: "i hope you meant [ps4]"
Jim: "damn autocorrelation" ❋ Bigfatsol (2014)
