Tag Archives: arma_1_1

Principal Components applied to Red Noise

We’ve obviously spent quite a bit of time analyzing the effect of the weird and incorrect MBH principal components method on red noise series. We’ve not argued that doing the principal components calculation correctly necessarily results in a meaningful index, only that doing it incorrectly cannot result in a meaningful index. One thing that I […]

Independent and Autocorrelated: Some Examples

I’ve been posting up on some fundamental articles on spurious regression, involving autocorrelated processes. Here are some illustrations of what different examples look like, with specific comment on a realclimate article.

A Pretty Graphic of ARMA Coefficients

Here is a plot of ARMA (1,1) coefficients for the CRU data set plotted up against a world map. I ‘ve not seen anything like this plotted up before. I think that the patterns are really quite pretty.

Jungle Fever

I tested some cells which were outliers under the ARMA(1,1) model. Here’s the result of the first cell that I looked at: the top panel shows the ACF – which has an unusual structure to say the least. The temperature anomaly plot is shown in the second panel and is also unusual to say the […]

ARMA (1,1) Coefficients for CRU Gridcells

I did an ARMA (1,1) on the CRU monthly (as opposed to the usual annual) global data set to see what it looked like. The ARMA (1,1) coefficients for the GL data for the second half of the data set were similar to those observed in the satellite data (AR1 +0.93; MA1 -0.46), but were […]

Arima on Surface Data

I’ve had a few references sent in to me on applications of arima to surface temperature series.

More on Satellite Arima: Vogelsang [1998]

A couple of days ago, I pointed out that the satellite GLB series could be modeled very well as a ARMA (1,1) model with parameters of AR1 = 0.9215 and MA1= -0.3185. I’ve gotten increasingly interested in ARMA (1,1) models with very high (>0.9 AR1 coefficients.) Vogelsang [1998] has some tables showing some very unexpected […]

Satellite Measurements #2: Arima

Here’s an interesting little graphic and analysis of the new satellite data. It’s hard not to scratch your head sometimes at this entire subject matter, when you see the effect of pretty simple alternatives. The satellite data is modelled very nicely as ARMA c(1,0,1), which would imply entirely different conclusions about this data set and […]

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