Sep 16, 2019 · 10 First, I think you mean what is the purpose of evaluating autocorrelation and dealing with it. If you really mean the "purpose of autocorrelation" then that's philosophy, not statistics. …

To account for spatial-autocorrelation, I have included latitude and longitude as a smoothed, interaction term (i.e. s (x,y)). I've based this on reading many papers where the authors say 'to account for …

Apr 19, 2023 · Interestingly with this small dataset, exp(pos + 0 |group) seems to work whether I define group as a dummy variable or as my site IDs, but with different results. In both cases, the …

You don't need to test for autocorrelation. It is there. The plot shows that. You could look at the autocorrelation function of these residuals (function acf()), but this will simply confirm what can be …

May 17, 2023 · I am familiar with computing the autocorrelation function of a time series as a function of time lag, but I am not sure what it means for a time series to itself be autocorrelated.

Let's try to rephrase this without using the terms serial correlation or autocorrelation. The dependent variable of a regression model has a conditional variance matrix, ie conditional on the independent …

I have calculated autocorrelation on time series data on the patterns of movement of a fish based on its positions: X (x.ts) and Y (y.ts). By using R, I ran the following functions and produced the

It seems that OLS residuals autocorrelation is not always an issue, depending on the problem at hand. But why residuals autocorrelation would affect the coefficient standard errors? From the Wikipe...

Nov 16, 2017 · I'm having a bit of trouble understanding the blue dotted lines in the following picture of autocorrelation function: Could someone give me a simple explanation, what they are telling me?

Apr 10, 2013 · I was wondering what does it mean when time series residuals have autocorrelation? How should I deal with it?