TY - GEN
T1 - The scale factor
T2 - Proceedings of the 2002 International Conference on Dependable Systems and Networks DNS 2002
AU - Bobbio, Andrea
AU - Horváth, András
AU - Telek, Miklós
N1 - Funding Information:
This work has been performed under the Italian-Hungarian R&D program supported by the Italian Ministry of Foreign Affairs and the Hungarian Ministry of Education. A. Bobbio and A. Horváth were partially supported by the MIUR under the project FIRB-Perf; M. Telek was partially supported by Hungarian Scientific Research Fund (OTKA) under Grant No. T-34972.
PY - 2002
Y1 - 2002
N2 - This paper introduces a unified approach to phase-type approximation in which the discrete and the continuous phase-type models form a common model set. The models of this common set are assigned with a non-negative real parameter, the scale factor. The case when the scale factor is strictly positive results in Discrete phase-type distributions and the scale factor represents the time elapsed in one step. If the scale factor is 0, the resulting class is the class of Continuous phase-type distributions. Applying the above view, it is shown that there is no qualitative difference between the discrete and the continuous phase-type models. Based on this unified view of phase-type models one can choose the best phase-type approximation of a stochastic model by optimizing the scale factor.
AB - This paper introduces a unified approach to phase-type approximation in which the discrete and the continuous phase-type models form a common model set. The models of this common set are assigned with a non-negative real parameter, the scale factor. The case when the scale factor is strictly positive results in Discrete phase-type distributions and the scale factor represents the time elapsed in one step. If the scale factor is 0, the resulting class is the class of Continuous phase-type distributions. Applying the above view, it is shown that there is no qualitative difference between the discrete and the continuous phase-type models. Based on this unified view of phase-type models one can choose the best phase-type approximation of a stochastic model by optimizing the scale factor.
KW - Approximate analysis
KW - Discrete and continuous phase type distributions
KW - Phase type expansion
UR - https://www.scopus.com/pages/publications/0036922087
U2 - 10.1109/DSN.2002.1029008
DO - 10.1109/DSN.2002.1029008
M3 - Conference contribution
AN - SCOPUS:0036922087
SN - 0769515975
SN - 9780769515977
T3 - Proceedings of the 2002 International Conference on Dependable Systems and Networks
SP - 627
EP - 636
BT - Proceedings of the 2002 International Conference on Dependable Systems and Networks
Y2 - 23 June 2002 through 26 June 2002
ER -