Markov and Semi-Markov Switching Linear Mixed Models Used to Identify Forest Tree Growth Components

Markov and semi-Markov switching linear mixed models used to identify forest tree growth components.

Tree growth is assumed to be mainly the result of three components: (i) an endogenous component assumed to be structured as a succession of roughly stationary phases separated by marked change points that are asynchronous among individuals, (ii) a time-varying environmental component assumed to take the form of synchronous fluctuations among individuals, and (iii) an individual component corres...

Estimating Markov and Semi-Markov Switching Linear Mixed Models with Individual-Wise Random Effects

We address the estimation of Markov (and semi-Markov) switching linear mixed models i.e. models that combine linear mixed models with individualwise random effects in a (semi-)Markovian manner. A MCEM-like algorithm whose iterations decompose into three steps (sampling of state sequences given random effects, prediction of random effects given the state sequence and maximization) is proposed. T...

Fads Models with Markov Switching Hetroskedasticity: decomposing Tehran Stock Exchange return into Permanent and Transitory Components

Stochastic behavior of stock returns is very important for investors and policy makers in the stock market. In this paper, the stochastic behavior of the return index of Tehran Stock Exchange (TEDPIX) is examined using unobserved component Markov switching model (UC-MS) for the 3/27/2010 until 8/3/2015 period. In this model, stock returns are decomposed into two components; a permanent componen...

Markov-Switching Models

Hidden semi-Markov models

Article history: Received 14 April 2009 Available online 17 November 2009