Yau-YauAL: A computer tool for solving nonlinear filtering problems
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866915336481144832 |
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| author | Wang, Yu Xu, Shuyuan Wei, Xueda Luo, Xinrui Yau, Stephen Shing-Toung Yau, Shing-Tung Wu, Rongling |
| author_facet | Wang, Yu Xu, Shuyuan Wei, Xueda Luo, Xinrui Yau, Stephen Shing-Toung Yau, Shing-Tung Wu, Rongling |
| contents | The Yau-Yau nonlinear filter has increasingly emerged as a powerful tool to study stochastic complex systems. To leverage it to a wider spectrum of application scenarios, we pack the Yau-Yau filtering ALgorithms (YauYauAL) into a package of computer software. Yau-YauAL was written in R, designed to simplify the implementation of the Yau-Yau filter for solving nonlinear filtering problems. Combining R's accessibility with C++ (via Rcpp) for computational efficiency, YauYauAL provides an intuitive Shiny-based interface that enables real-time parameter adjustment and result visualization. At its core, YauYauAL employs finite difference methods to numerically solve the Kolmogorov forward equation, ensuring a stable and accurate solution even for complex systems. YauYauAL's modular design and open-source framework further encourage customization and community-driven development. YauYauAL aims to bridge the gap between theoretical nonlinear filtering methods and practical applications, without requiring expertise in differential equation solving or programming, fostering its broader impact on various scientific fields, such as signal processing, finance, medicine, and biology among a long list. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2506_08976 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Yau-YauAL: A computer tool for solving nonlinear filtering problems Wang, Yu Xu, Shuyuan Wei, Xueda Luo, Xinrui Yau, Stephen Shing-Toung Yau, Shing-Tung Wu, Rongling Applications 93E11, 60G35 D.2.12 The Yau-Yau nonlinear filter has increasingly emerged as a powerful tool to study stochastic complex systems. To leverage it to a wider spectrum of application scenarios, we pack the Yau-Yau filtering ALgorithms (YauYauAL) into a package of computer software. Yau-YauAL was written in R, designed to simplify the implementation of the Yau-Yau filter for solving nonlinear filtering problems. Combining R's accessibility with C++ (via Rcpp) for computational efficiency, YauYauAL provides an intuitive Shiny-based interface that enables real-time parameter adjustment and result visualization. At its core, YauYauAL employs finite difference methods to numerically solve the Kolmogorov forward equation, ensuring a stable and accurate solution even for complex systems. YauYauAL's modular design and open-source framework further encourage customization and community-driven development. YauYauAL aims to bridge the gap between theoretical nonlinear filtering methods and practical applications, without requiring expertise in differential equation solving or programming, fostering its broader impact on various scientific fields, such as signal processing, finance, medicine, and biology among a long list. |
| title | Yau-YauAL: A computer tool for solving nonlinear filtering problems |
| topic | Applications 93E11, 60G35 D.2.12 |
| url | https://arxiv.org/abs/2506.08976 |