Statistical estimation of parameters in Markov processes

Statistical Inference : in Markov - Renewal Processes

The undesirable prospect of increasing congestion un the nation'sairways has caused attention to be focused more and more on terminalareas. Two distinct efforts to improve traffic flow have been studiedelsewhere. One, by means of careful control of aircraft separationalong flight paths leading to the terminal, runways attempts to reduceflow variability, while the other attem...

Fuzzy Estimation of Parameters in Statistical Models

Using a set of confidence intervals, we develop a common approach, to construct a fuzzy set as an estimator for unknown parameters in statistical models. We investigate a method to derive the explicit and unique membership function of such fuzzy estimators. The proposed method has been used to derive the fuzzy estimators of the parameters of a Normal distribution and some functions of parameter...

The KTH Visit in Semi-Markov Processes

Generator estimation of Markov jump processes q

Estimating the generator of a continuous-time Markov jump process based on incomplete data is a problem which arises in various applications ranging from machine learning to molecular dynamics. Several methods have been devised for this purpose: a quadratic programming approach (cf. [D.T. Crommelin, E. Vanden-Eijnden, Fitting timeseries by continuous-time Markov chains: a quadratic programming ...

Generator estimation of Markov jump processes

Philipp Metzner, Evelyn Dittmer, Tobias Jahnke, Christof Schütte Institute of Mathematics II, Free University Berlin, Arnimallee 2-6, D-14195 Berlin, Germany (Dated: March 5, 2007) Abstract Recently, two new methods have been presented for the estimation of an infinitesimal generator of a Markov jump process from an incomplete observation. The first approach, introduced by Crommelin and Vanden-...