Kalman Filter of Dynamic Hierarchical Model

Abstract

This research attempted to derive a mathematical formula to calculate Kalman Filter for a hierarchical kinetic model. This formula formed an iterative procedure to estimate parameters of the model in question, and reduce errors associated with it to get an optimal estimate of the parameters. This research concluded that the results that were derived could be applied in general when variance matrices were identified, which was practically rare, so, appropriate measures should be available in the data under study to allow variance to be estimated; and the technique proposed for application can be used for one set of data (i.e., i=1), and can be generalized to more than data sets.