An Extension of Yoshida, Imoto, Higuchi and Miyano Result

Problem statement: Different approaches to deal with dynamic model when it is studentized are presented. Approach: In this respect, the recursive formula for calculating state space in the canonical form. Results: The asymptotic distribution of their test under the linear system for the gene network and a studentized-dynamic linear model with Markov denoising switching for estimating time-dependent gene network structure were presented. A resultant studentized version for gene network state space model was obtained, as an improvement on the original model. Conclusion/Recommendations: The dynamic model with Markov switching for estimating time-dependent gene regulatory networks handled the problem of modeling change in an evolving time series. The studentized version incorporated the modeling change and test for heteroscedasticity