In my previous blog post I demonstrated how to implement and use the extended Kalman filter (EKF) in R. In this post I will show how to predict future system states and observations with the EKF. Continue reading R code for forecasting with the extended Kalman filter
In my previous blog post I showed how to implement and use the extended Kalman filter (EKF) in R. In this post I will demonstrate how to fit unknown parameters of an EKF model by means of likelihood maximization. Continue reading R code for estimating the parameters of an extended Kalman filter model using likelihood maximization
The code below implements the discrete-time extended Kalman filter (EKF) in R.
For numerical stability and precision the implemented EKF uses a Singular Value Decomposition (SVD) based square root filter. For a description of this SVD-based square root filter see Appendix B of Petris and colleagues’ 2009 book Dynamic linear models with R. Continue reading R code for implementing the extended Kalman filter