Differentiation formulas for probability functions: The transformation method
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Publication:1363426
DOI10.1007/BF02592152zbMath0905.90128OpenAlexW1982045540MaRDI QIDQ1363426
Publication date: 7 August 1997
Published in: Mathematical Programming. Series A. Series B (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/bf02592152
probabilistic programmingtransformation techniquestructural reliabilitydifferentiation of integralsstochastic completion method
Related Items (9)
A discussion of probability functions and constraints from a variational perspective ⋮ Application of the Smooth Approximation of the Probability Function in Some Applied Stochastic Programming Problems ⋮ Decomposition methods in stochastic programming ⋮ Gradient formulae for probability functions depending on a heterogenous family of constraints ⋮ An Inner-Outer Approximation Approach to Chance Constrained Optimization ⋮ A characterization of the subdifferential of singular Gaussian distribution functions ⋮ Extensions of stochastic optimization results to problems with system failure probability functions ⋮ Analytic approximation and differentiability of joint chance constraints ⋮ Advances and applications of chance-constrained approaches to systems optimisation under uncertainty
Cites Work
- Sensitivity analysis of discrete event systems by the push out method
- Bonferroni inequalities
- Asymptotic approximations for multivariate integrals with an application to multinormal probabilities
- Evaluation of a special multivariate gamma distribution function
- A differentiation formula for integrals overseas given by inclusion
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