TDA

R package TDA: Statistical Tools for Topological Data Analysis. Tools for the statistical analysis of persistent homology and for density clustering. For that, this package provides an R interface for the efficient algorithms of the C++ libraries GUDHI, Dionysus, and PHAT.

Keywords for this software

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References in zbMATH (referenced in 24 articles , 1 standard article )

Showing results 1 to 20 of 24.
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  1. Loliencar, Prachi; Heo, Giseon: Phenotyping OSA: a time series analysis using fuzzy clustering and persistent homology (2022)
  2. Zhao, Yan; Wang, Yanying; Ding, Yanhong; Han, Huiyun: Topological data analysis for the energy and stability of endohedral metallofullerenes (2022)
  3. Aromi, Lloyd L.; Katz, Yuri A.; Vives, Josep: Topological features of multivariate distributions: dependency on the covariance matrix (2021)
  4. Ciocanel, Maria-Veronica; Juenemann, Riley; Dawes, Adriana T.; McKinley, Scott A.: Topological data analysis approaches to uncovering the timing of ring structure onset in filamentous networks (2021)
  5. Padellini, Tullia; Brutti, Pierpaolo: Supervised learning with indefinite topological kernels (2021)
  6. Wang, Rui; Zhao, Rundong; Ribando-Gros, Emily; Chen, Jiahui; Tong, Yiying; Wei, Guo-Wei: HERMES: persistent spectral graph software (2021)
  7. Biscio, Christophe A. N.; Chenavier, Nicolas; Hirsch, Christian; Svane, Anne Marie: Testing goodness of fit for point processes via topological data analysis (2020)
  8. Bramer, David; Wei, Guo-Wei: Atom-specific persistent homology and its application to protein flexibility analysis (2020)
  9. Brécheteau, Claire; Levrard, Clément: A (k)-points-based distance for robust geometric inference (2020)
  10. Bubenik, Peter: The persistence landscape and some of its properties (2020)
  11. Gidea, Marian; Goldsmith, Daniel; Katz, Yuri; Roldan, Pablo; Shmalo, Yonah: Topological recognition of critical transitions in time series of cryptocurrencies (2020)
  12. Som, Anirudh; Ramamurthy, Karthikeyan Natesan; Turaga, Pavan: Geometric metrics for topological representations (2020)
  13. Vandaele, Robin; Saeys, Yvan; De Bie, Tijl: Mining topological structure in graphs through forest representations (2020)
  14. Maroulas, Vasileios; Mike, Joshua L.; Oballe, Christopher: Nonparametric estimation of probability density functions of random persistence diagrams (2019)
  15. Mémoli, Facundo; Singhal, Kritika: A primer on persistent homology of finite metric spaces (2019)
  16. Patrangenaru, Vic; Bubenik, Peter; Paige, Robert L.; Osborne, Daniel: Challenges in topological object data analysis (2019)
  17. Alan Hylton, Gregory Henselman-Petrusek, Janche Sang, Robert Short: Tuning the Performance of a Computational Persistent Homology Package (2018) arXiv
  18. Chazal, Frédéric; Fasy, Brittany; Lecci, Fabrizio; Michel, Bertrand; Rinaldo, Alessandro; Wasserman, Larry: Robust topological inference: distance to a measure and kernel distance (2018)
  19. Marchese, Andrew; Maroulas, Vasileios: Signal classification with a point process distance on the space of persistence diagrams (2018)
  20. Moon, Chul; Giansiracusa, Noah; Lazar, Nicole A.: Persistence terrace for topological inference of point cloud data (2018)

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