TY - JOUR
T1 - Exact predictive likelihood inference for Laplace distribution based on a time-constrained experiment
AU - Zhu, Xiaojun
AU - Balakrishnan, Narayanaswamy
AU - Zhou, Yiliang
AU - So, Hon Yiu
N1 - Publisher Copyright:
© 2019, © 2019 Taylor & Francis Group, LLC.
PY - 2020/3/3
Y1 - 2020/3/3
N2 - In this paper, we will first derive explicit expressions for the predictive maximum likelihood estimators (PMLEs) for Laplace distribution based on a time-constrained life-testing experiment. Next, we derive the exact conditional distribution of the likelihood predictor of the s-th failure through the use of exact conditional moment generating function (MGF). We develop three different exact prediction intervals for the future failure, and a Monte Carlo simulation study is then carried out to check the accuracy of the derived exact inference. Finally, an example is presented to illustrate all the inferential results developed here.
AB - In this paper, we will first derive explicit expressions for the predictive maximum likelihood estimators (PMLEs) for Laplace distribution based on a time-constrained life-testing experiment. Next, we derive the exact conditional distribution of the likelihood predictor of the s-th failure through the use of exact conditional moment generating function (MGF). We develop three different exact prediction intervals for the future failure, and a Monte Carlo simulation study is then carried out to check the accuracy of the derived exact inference. Finally, an example is presented to illustrate all the inferential results developed here.
KW - Conditional moment generating function
KW - Laplace distribution
KW - Prediction interval
KW - Predictive maximum likelihood estimators
KW - Type-I censoring
UR - http://www.scopus.com/inward/record.url?scp=85081113180&partnerID=8YFLogxK
U2 - 10.1080/03610918.2019.1642480
DO - 10.1080/03610918.2019.1642480
M3 - Article
AN - SCOPUS:85081113180
SN - 0361-0918
VL - 49
SP - 647
EP - 668
JO - Communications in Statistics: Simulation and Computation
JF - Communications in Statistics: Simulation and Computation
IS - 3
ER -