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I've got an irregularly spaced time series with regressors. I've found the R packages cts and ctsem for continuous time series, but they don't allow for exogenous variables. Is it possible to have both features in the same model?

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  • $\begingroup$ Look into gaussian processes or even 1D kriging $\endgroup$ – kjetil b halvorsen Jul 18 at 18:33
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The documentation for ctsem says it can handle time-dependent and time-independent exogenous variables.

Here is some of the documentation, there is much more. Hierarchical Bayesian Continuous-Time Dynamic Modeling https://www.researchgate.net/publication/310747801_Hierarchical_Bayesian_Continuous_Time_Dynamic_Modeling

See page 6.

Subject level latent dynamic modelThe subject level dynamics are described by the stochastic differential equation:$$dη(t)=Aη(t)+b+Mχ(t)dt+GdW(t)$$ (1)

In Equation 1 the time-dependent predictors χ(t) represent exogenous inputs to the system, such as an intervention, that may vary over time and are independent of fluctuations in the system

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  • $\begingroup$ Hello there. To help people understand your answer, and make it compliant with our community rules, you could improve on the format of your answer. Use latex for the equation written in your answer. I couldn't improve much, since I don't the subject, nor have I acess to the pdf right now... $\endgroup$ – An old man in the sea. Jul 18 at 18:51

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