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

# Tag: nonlinear dynamic model

## R code for estimating the parameters of an extended Kalman filter model using likelihood maximization

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

## R code for implementing the extended Kalman filter

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