Asymptotic normality for discretely observed Markov jump processes with an absorbing state

Alexander Kremer and Rafael Weißbach

Statistics & Probability Letters, 2014, vol. 90, issue C, 136-139

Abstract: For a continuous-time Markov process, occasionally, only discrete-time observations are available. For a simple sample of homogeneous Markov jump processes with an absorbing state, observed each on a stochastic grid of time points, we establish asymptotic normality of the maximum likelihood estimator and close the gap in Kremer and Weißbach (2013). By showing that the solution of the Kolmogorov backward equation system is continuous differentiable, we can apply results for M-estimators.

Keywords: Multiple Markov jump process; Discrete observations; Asymptotic normality; Parametric maximum likelihood (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (3)

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DOI: 10.1016/j.spl.2014.03.010

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