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The purpose of this paper is to introduce a class of stochastic processes that we call step semi-Markov processes and to illustrate the modelling capacity of such processes in practical applications. The name of this process comes from the fact that we have a semi-Markov process and the transition between two states is done through several steps. We first introduce these models and the main quantities that characterize them. Then, we derive the recursive evolution equations for two-step semi-Markov processes. The interest of using this type of model is illustrated by means of an application in manpower planning.
Barbu, Vlad Stefan 1 ; D’Amico, Guglielmo 2 ; Manca, Raimondo 3 ; Petroni, Filippo 4
@article{PS_2016__20__555_0, author = {Barbu, Vlad Stefan and D{\textquoteright}Amico, Guglielmo and Manca, Raimondo and Petroni, Filippo}, title = {Step {semi-Markov} models and application to manpower management}, journal = {ESAIM: Probability and Statistics}, pages = {555--571}, publisher = {EDP-Sciences}, volume = {20}, year = {2016}, doi = {10.1051/ps/2016025}, mrnumber = {3581834}, zbl = {1356.60139}, language = {en}, url = {http://geodesic.mathdoc.fr/articles/10.1051/ps/2016025/} }
TY - JOUR AU - Barbu, Vlad Stefan AU - D’Amico, Guglielmo AU - Manca, Raimondo AU - Petroni, Filippo TI - Step semi-Markov models and application to manpower management JO - ESAIM: Probability and Statistics PY - 2016 SP - 555 EP - 571 VL - 20 PB - EDP-Sciences UR - http://geodesic.mathdoc.fr/articles/10.1051/ps/2016025/ DO - 10.1051/ps/2016025 LA - en ID - PS_2016__20__555_0 ER -
%0 Journal Article %A Barbu, Vlad Stefan %A D’Amico, Guglielmo %A Manca, Raimondo %A Petroni, Filippo %T Step semi-Markov models and application to manpower management %J ESAIM: Probability and Statistics %D 2016 %P 555-571 %V 20 %I EDP-Sciences %U http://geodesic.mathdoc.fr/articles/10.1051/ps/2016025/ %R 10.1051/ps/2016025 %G en %F PS_2016__20__555_0
Barbu, Vlad Stefan; D’Amico, Guglielmo; Manca, Raimondo; Petroni, Filippo. Step semi-Markov models and application to manpower management. ESAIM: Probability and Statistics, Tome 20 (2016), pp. 555-571. doi: 10.1051/ps/2016025
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