Autocorrelation not as expected

1. Does autocorrelation affect prediction?
2. What is the problem with autocorrelation?
3. How do you know if autocorrelation is significant?
4. What does it mean if there is no autocorrelation?

Does autocorrelation affect prediction?

A reason you may care about autocorrelation is because it can give you biased parameter estimates meaning your predictions may not be as accurate as they could be!

What is the problem with autocorrelation?

Autocorrelation can cause problems in conventional analyses (such as ordinary least squares regression) that assume independence of observations. In a regression analysis, autocorrelation of the regression residuals can also occur if the model is incorrectly specified.

How do you know if autocorrelation is significant?

Another check is an autocorrelation plot that shows the autocorrelations for various lags. Confidence bands can be plotted at the 95 % and 99 % confidence levels. Points outside this band indicate statistically significant values (lag 0 is always 1).

What does it mean if there is no autocorrelation?

Specifically, the CLRM assumes there's no autocorrelation.</p>\n<p><i>No autocorrelation</i> refers to a situation in which no identifiable relationship exists between the values of the error term.