Markov-Modulated Linear Regression
arXiv:1901.09600
Abstract
Classical linear regression is considered for a case when regression parameters depend on the external random environment. The last is described as a continuous time Markov chain with finite state space. Here the expected sojourn times in various states are additional regressors. Necessary formulas for an estimation of regression parameters have been derived. The numerical example illustrates the results obtained.
In proceedings book: International conference on Statistical Models and Methods for Reliability and Survival Analysis and Their Validation (S2MRSA), 5 pages