Bayesian and Nonparametric Bayesian Optimal Designs With the Length of Interconnected Intervals for Unit Exponential Regression Model.
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| Title: | Bayesian and Nonparametric Bayesian Optimal Designs With the Length of Interconnected Intervals for Unit Exponential Regression Model. |
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| Authors: | Khazaei, Soleiman1 (AUTHOR) soleimank@gmail.com, Abdollahi Nanvapisheh, Anita1 (AUTHOR), Jafari, Habib1 (AUTHOR), Sen, Smritijit1 (AUTHOR) smsen@wiley.com |
| Source: | Journal of Probability & Statistics. 7/9/2026, Vol. 2026, p1-11. 11p. |
| Subjects: | Optimal designs (Statistics), Bayesian analysis, Regression analysis, Nonlinear regression |
| Abstract: | Nonlinear regression models are widely utilized in many scientific disciplines. Precisely estimating an optimal nonlinear regression model is critical, especially when considering potential biases may arise in Bayesian optimal design. The current work introduces Bayesian and nonparametric Bayesian optimal designs based on the length of interconnected intervals for the unit exponential (UE) regression model. In cases where parameter information or historical data are limited, a nonparametric Bayesian method is employed through placing a Dirichlet process (DP) prior on the space of distribution functions. Lastly, the efficiency of various optimal designs is assessed and compared. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | Nonlinear regression models are widely utilized in many scientific disciplines. Precisely estimating an optimal nonlinear regression model is critical, especially when considering potential biases may arise in Bayesian optimal design. The current work introduces Bayesian and nonparametric Bayesian optimal designs based on the length of interconnected intervals for the unit exponential (UE) regression model. In cases where parameter information or historical data are limited, a nonparametric Bayesian method is employed through placing a Dirichlet process (DP) prior on the space of distribution functions. Lastly, the efficiency of various optimal designs is assessed and compared. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 1687952X |
| DOI: | 10.1155/jpas/8892090 |
