TY - GEN
T1 - Model selection with application to gamma process and inverse Gaussian process
AU - Zhang, Mimi
AU - Revie, Matthew
N1 - This is an Accepted Manuscript of a book chapter published by CRC Press in Risk, Reliability and Safety: Innovating Theory and Practice: Proceedings of ESREL 2016 (Glasgow, Scotland, 25-29 September 2016) on 13/09/2016, available : https://www.crcpress.com/Risk-Reliability-and-Safety-Innovating-Theory-and-Practice-Proceedings/Walls-Revie-Bedford/p/book/9781138029972
PY - 2016/9/13
Y1 - 2016/9/13
N2 - The gamma process and the inverse Gaussian process are widely used in condition-based maintenance. Both are suitable for modelling monotonically increasing degradation processes. One challenge for practitioners is determining which of the two processes is most appropriate in light of a real data set. A common practice is to select the one with a larger maximized likelihood. However, due to variations in the data, the maximized likelihood of the “wrong” model could be larger than that of the “right” model. This paper proposes an efficient and broadly applicable test statistic for model selection. The construction of the test statistic is based on the Fisher information. Extensive numerical study is conducted to indicate the conditions under which the gamma process can be well approximated by the inverse Gaussian process, or the other way around.
AB - The gamma process and the inverse Gaussian process are widely used in condition-based maintenance. Both are suitable for modelling monotonically increasing degradation processes. One challenge for practitioners is determining which of the two processes is most appropriate in light of a real data set. A common practice is to select the one with a larger maximized likelihood. However, due to variations in the data, the maximized likelihood of the “wrong” model could be larger than that of the “right” model. This paper proposes an efficient and broadly applicable test statistic for model selection. The construction of the test statistic is based on the Fisher information. Extensive numerical study is conducted to indicate the conditions under which the gamma process can be well approximated by the inverse Gaussian process, or the other way around.
KW - gamma process
KW - Gaussian process
KW - condition-based maintenance
KW - degradation processes
KW - Fisher information matrix
UR - https://www.crcpress.com/Risk-Reliability-and-Safety-Innovating-Theory-and-Practice-Proceedings/Walls-Revie-Bedford/p/book/9781138029972
UR - http://esrel2016.org/
M3 - Conference contribution book
SN - 9781138029972
BT - Risk, Reliability and Safety
A2 - Walls, Lesley
A2 - Revie, Matthew
A2 - Bedford, Time
CY - London, UK
ER -