PATSYM

PATSYM: A set of Fortran subroutines, with sample driver program, for the numerical integration of a vector of integrals over a hyper-rectangular region. This software uses the integration rules described in the paper by Alan Genz, Fully Symmetric Interpolatory Rules for Multiple Integrals, SIAM J. Numer. Anal. 23 (1986), pp. 1273-1283.

Keywords for this software

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References in zbMATH (referenced in 45 articles , 1 standard article )

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  1. Bayer, Christian; Siebenmorgen, Markus; Tempone, Raul: Smoothing the payoff for efficient computation of basket option prices (2018)
  2. Chen, Peng: Sparse quadrature for high-dimensional integration with Gaussian measure (2018)
  3. Ernst, Oliver G.; Sprungk, Björn; Tamellini, Lorenzo: Convergence of sparse collocation for functions of countably many Gaussian random variables (with application to elliptic PDEs) (2018)
  4. Farcas, Ionut-Gabriel; Uekermann, Benjamin; Neckel, Tobias; Bungartz, Hans-Joachim: Nonintrusive uncertainty analysis of fluid-structure interaction with spatially adaptive sparse grids and polynomial chaos expansion (2018)
  5. Bourquin, Raoul: Algorithms for the construction of high-order Kronrod rule extensions with application to sparse-grid integration (2017)
  6. Kolassa, John E.; Robinson, John: Nonparametric tests for multi-parameter $M$-estimators (2017)
  7. Liao, Qinzhuo; Zhang, Dongxiao; Tchelepi, Hamdi: A two-stage adaptive stochastic collocation method on nested sparse grids for multiphase flow in randomly heterogeneous porous media (2017)
  8. Barajas-Solano, David A.; Tartakovsky, Daniel M.: Stochastic collocation methods for nonlinear parabolic equations with random coefficients (2016)
  9. Ko, Jordan; Wynn, Henry P.: The algebraic method in quadrature for uncertainty quantification (2016)
  10. Król, Agnieszka; Ferrer, Loïc; Pignon, Jean-Pierre; Proust-Lima, Cécile; Ducreux, Michel; Bouché, Olivier; Michiels, Stefan; Rondeau, Virginie: Joint model for left-censored longitudinal data, recurrent events and terminal event: predictive abilities of tumor burden for cancer evolution with application to the FFCD 2000--05 trial (2016)
  11. Nobile, Fabio; Tamellini, Lorenzo; Tesei, Francesco; Tempone, Raúl: An adaptive sparse grid algorithm for elliptic PDEs with lognormal diffusion coefficient (2016)
  12. Rahman, Sharif; Ren, Xuchun; Yadav, Vaibhav: High-dimensional stochastic design optimization by adaptive-sparse polynomial dimensional decomposition (2016)
  13. Chen, Michael; Mehrotra, Sanjay; Papp, Dávid: Scenario generation for stochastic optimization problems via the sparse grid method (2015)
  14. Lei, H.; Yang, X.; Zheng, B.; Lin, G.; Baker, N. A.: Constructing surrogate models of complex systems with enhanced sparsity: quantifying the influence of conformational uncertainty in biomolecular solvation (2015)
  15. Liao, Qinzhuo; Zhang, Dongxiao: Constrained probabilistic collocation method for uncertainty quantification of geophysical models (2015)
  16. Samonenko, Inga; Robinson, John: A new permutation test statistic for complete block designs (2015)
  17. Da Fonseca, José; Grasselli, Martino; Ielpo, Florian: Estimating the Wishart affine stochastic correlation model using the empirical characteristic function (2014)
  18. Geraci, Marco; Bottai, Matteo: Linear quantile mixed models (2014)
  19. Yadav, Vaibhav; Rahman, Sharif: Adaptive-sparse polynomial dimensional decomposition methods for high-dimensional stochastic computing (2014)
  20. Zhang, Xin-Chun; Teng, Yun-Long: A new derivation of the cubature Kalman filters (2014)

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