Please also provide the following information in addition to your question: I used this autocorrelation cor_ar structure for my time series data. However, I think it is more meant for evenly spaced data, while my data, as well as many other data, are more likely to be unevenly spaced, I believe. Wi…

With you first question you are refering to continuous time autoregressive models. This might get implemented at some point in brms, but is likely far away in the future (if it will ever come). You may want to look at the ctsem R package which handles continuous time models and can also use Stan as …

If you are using mgcv, then you can use the correlation structure corCAR1 in the gamm function. One of the few things I miss in brms.

I think the OP was thinking of a continuous-time analogue of the cor_ar() correlation structure rather than an entire continuous-time model. An example would be be nlme::corCAR1(), which is a special case of an exponential spatial correlation structure. Pinheiro & Bates (2000; Mixed-Effects Models…

Yeah that makes sense. Would you mind opening an issue about this on github so that I don’t forget about this feature?

For reference, I opened this as issue #741

If anyone comes across this and is still looking for a solution (I don’t believe it is available in {brms} yet, you can implement the continuous time AR1 model (exactly as @ucfagls defines it above) in the {mvgam} package . A short example is shown below library(mvgam) library(ggplot2); theme_set(th…

Autocorrelation for unevenly spaced time series

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ucfagls August 27, 2019, 2:50pm 6

Thanks Paul. Will do this afternoon.

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Autocorrelation for unevenly spaced time series

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