Specifying prior distributions in reliability applications
Especially when facing reliability data with limited information (eg, a small number of
failures), there are strong motivations for using Bayesian inference methods. These include …
failures), there are strong motivations for using Bayesian inference methods. These include …
Methods to compute prediction intervals: A review and new results
Methods to Compute Prediction Intervals: A Review and New Results Page 1 Statistical Science
2022, Vol. 37, No. 4, 580–597 https://doi.org/10.1214/21-STS842 © Institute of Mathematical …
2022, Vol. 37, No. 4, 580–597 https://doi.org/10.1214/21-STS842 © Institute of Mathematical …
Optimality of thompson sampling with noninformative priors for pareto bandits
In the stochastic multi-armed bandit problem, a randomized probability matching policy
called Thompson sampling (TS) has shown excellent performance in various reward …
called Thompson sampling (TS) has shown excellent performance in various reward …
The Choice of Noninformative Priors for Thompson Sampling in Multiparameter Bandit Models
J Lee, CK Chiang, M Sugiyama - … of the AAAI Conference on Artificial …, 2024 - ojs.aaai.org
Thompson sampling (TS) has been known for its outstanding empirical performance
supported by theoretical guarantees across various reward models in the classical …
supported by theoretical guarantees across various reward models in the classical …
Prediction interval methods for reliability data
Q Tian - 2021 - search.proquest.com
Prediction interval methods for reliability data by Qinglong Tian A dissertation submitted to the
graduate faculty in partial fu Page 1 Prediction interval methods for reliability data by Qinglong …
graduate faculty in partial fu Page 1 Prediction interval methods for reliability data by Qinglong …