Dimensionality Reduction of Sliced-Normal Distributions

Author:

Crespo Luis G.,Colbert Brendon K.,Kenny Sean P.,Giesy Daniel P.

Publisher

Elsevier BV

Subject

Control and Systems Engineering

Reference8 articles.

1. Colbert, B., Crespo, L., and M., P. (2020). Improved uncertainty quantification for sliced normal distributions of increasing degree and dimension. American Control Conference.

2. On the quantification of aleatory and epistemic uncertainty using sliced-normal distributions;Crespo;Systems and Control Letters,2019

3. Crespo, L.G., Giesy, D., Kenny, S., and Deride, J. (2019b). A scenario optimization approach to system identification with reliability guarantees. American Control Conference.

4. Analyzing dependent data with vine copulas;Czado,2019

5. Parameter estimation for pair-copula constructions;Haff,2013

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1. A distributionally robust data-driven framework to reliability analysis;Structural Safety;2024-11

2. An Inverse Chance-Constrained Approach to the Calibration of Robust Models;2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC);2023-10-01

3. Robust Estimation of Sliced-Exponential Distributions;2021 60th IEEE Conference on Decision and Control (CDC);2021-12-14

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