<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title>Bing: Autocorrelation Definition</title><link>http://www.bing.com:80/search?q=Autocorrelation+Definition</link><description>Search results</description><image><url>http://www.bing.com:80/s/a/rsslogo.gif</url><title>Autocorrelation Definition</title><link>http://www.bing.com:80/search?q=Autocorrelation+Definition</link></image><copyright>Copyright © 2026 Microsoft. All rights reserved. These XML results may not be used, reproduced or transmitted in any manner or for any purpose other than rendering Bing results within an RSS aggregator for your personal, non-commercial use. Any other use of these results requires express written permission from Microsoft Corporation. By accessing this web page or using these results in any manner whatsoever, you agree to be bound by the foregoing restrictions.</copyright><item><title>autocorrelation - What does it mean for a time series to be ...</title><link>https://stats.stackexchange.com/questions/616173/what-does-it-mean-for-a-time-series-to-be-autocorrelated</link><description>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.</description><pubDate>Tue, 31 Mar 2026 10:06:00 GMT</pubDate></item><item><title>lme4 nlme - How to deal with spatial autocorrelation AND temporal ...</title><link>https://stats.stackexchange.com/questions/561669/how-to-deal-with-spatial-autocorrelation-and-temporal-autocorrelation-in-a-mixed</link><description>When creating a mixed model (or GLS) with spatiotemporal data, you can include correlation structure into your model to address autocorrelation. Spatial autocorrelation can be modelled for with</description><pubDate>Wed, 01 Apr 2026 17:07:00 GMT</pubDate></item><item><title>How to test the autocorrelation of the residuals?</title><link>https://stats.stackexchange.com/questions/14914/how-to-test-the-autocorrelation-of-the-residuals</link><description>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 seen by plain eye: the correlations between lagged residuals are very high.</description><pubDate>Wed, 01 Apr 2026 19:44:00 GMT</pubDate></item><item><title>Spatial autocorrelation correction with glmmTMB - Cross Validated</title><link>https://stats.stackexchange.com/questions/613457/spatial-autocorrelation-correction-with-glmmtmb</link><description>The help info says you can have residual spatial autocorrelation even if the model takes care of it. I added the command rotation="estimated" during the recalculation and the autocorrelation is no longer statistically significant.</description><pubDate>Fri, 03 Apr 2026 01:20:00 GMT</pubDate></item><item><title>Autocorrelation vs Non-stationary - Cross Validated</title><link>https://stats.stackexchange.com/questions/167737/autocorrelation-vs-non-stationary</link><description>What is the relationship between autocorrelation and non-stationary? Is it true that non-zero autocorrelation $\\implies$ non-stationary, but not vice versa?</description><pubDate>Fri, 03 Apr 2026 07:39:00 GMT</pubDate></item><item><title>Autocorrelation in linear mixed models (lme) - Cross Validated</title><link>https://stats.stackexchange.com/questions/475950/autocorrelation-in-linear-mixed-models-lme</link><description>I disagree that autocorrelation and random intercept are redundant. The random intercept would be a difference in mean for that group (e.g., whale) compared to the whole population, which could be present with or without serial autocorrelation within that group.</description><pubDate>Wed, 01 Apr 2026 19:37:00 GMT</pubDate></item><item><title>time series - How to interpret autocorrelation of residuals and what to ...</title><link>https://stats.stackexchange.com/questions/55658/how-to-interpret-autocorrelation-of-residuals-and-what-to-do-with-it</link><description>I was wondering what does it mean when time series residuals have autocorrelation? How should I deal with it?</description><pubDate>Fri, 03 Apr 2026 12:32:00 GMT</pubDate></item><item><title>What's the deal with autocorrelation? - Cross Validated</title><link>https://stats.stackexchange.com/questions/49265/whats-the-deal-with-autocorrelation</link><description>So why is autocorrelation a bad (or good) thing? 2.) The solution I've heard for dealing with autocorrelation is to diff the time series. Without trying to read the author's mind, why would one not do a diff if non-negligible autocorrelation exists? 3.) What limitations do non-negligible autocorrelations place on a model?</description><pubDate>Thu, 02 Apr 2026 10:18:00 GMT</pubDate></item><item><title>How to deal with autocorrelation in mixed models</title><link>https://stats.stackexchange.com/questions/475806/how-to-deal-with-autocorrelation-in-mixed-models</link><description>I tried first to apply a linear mixed model (lme) and I had a problem of autocorrelation and non-normality of residuals. Next, I tried to apply a GLM with Poisson and negative binomial distributions. Both had the same problem of autocorrelation and/or non-normality of residuals. What can I do to model these variables or to correct these issues?</description><pubDate>Wed, 01 Apr 2026 18:26:00 GMT</pubDate></item><item><title>What's the difference between multicollinearity and autocorrelation?</title><link>https://stats.stackexchange.com/questions/496034/whats-the-difference-between-multicollinearity-and-autocorrelation</link><description>Additionally, if I made a model and I wanna validate the conditions necessary for it to be a good model, should I test both conditions (multicollinearity and autocorrelation)? or only one of those.</description><pubDate>Sat, 04 Apr 2026 12:24:00 GMT</pubDate></item></channel></rss>