Armadillo is a C++ linear algebra library (matrix maths) aiming towards a good balance between speed and ease of use. Integer, floating point, and complex numbers are supported, as well as a subset of trigonometric and statistics functions. Various matrix decompositions are provided through optional integration with LAPACK and ATLAS libraries. A delayed evaluation approach, based on template meta-programming, is used (during compile time) to combine several operations into one and reduce or eliminate the need for temporaries. (Source:

References in zbMATH (referenced in 69 articles )

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  1. Daniel Peña, Ezequiel Smucler, Victor Yohai: gdpc: An R Package for Generalized Dynamic Principal Components (2020) not zbMATH
  2. Donald Williams; Joris Mulder: BGGM: Bayesian Gaussian Graphical Models in R (2020) not zbMATH
  3. Florez, Horacio; Gildin, Eduardo: Global/local model order reduction in coupled flow and linear thermal-poroelasticity (2020)
  4. Hessenthaler, Andreas; Southworth, Ben S.; Nordsletten, David; Röhrle, Oliver; Falgout, Robert D.; Schroder, Jacob B.: Multilevel convergence analysis of multigrid-reduction-in-time (2020)
  5. Kisung You, Changhee Suh: Rdimtools: An R package for Dimension Reduction and Intrinsic Dimension Estimation (2020) arXiv
  6. Lukas Riedel; Benjamin Herdeanu; Harald Mack; Yunus Sevinchan; Julian Weninger: Utopia: A Comprehensive and Collaborative Modeling Framework for Complex and Evolving Systems (2020) not zbMATH
  7. Markus Frings, Norbert Hosters, Corinna Müller, Max Spahn, Christoph Susen, Konstantin Key, Stefanie Elgeti: SplineLib: A Modern Multi-Purpose C++ Spline Library (2020) arXiv
  8. Reguly, István Z.; Mudalige, Gihan R.: Productivity, performance, and portability for computational fluid dynamics applications (2020)
  9. David Ardia; Kris Boudt; Leopoldo Catania: Generalized Autoregressive Score Models in R: The GAS Package (2019) not zbMATH
  10. Heck, Daniel W.; Davis-Stober, Clintin P.: Multinomial models with linear inequality constraints: overview and improvements of computational methods for Bayesian inference (2019)
  11. Heck, Daniel W.; Overstall, Antony M.; Gronau, Quentin F.; Wagenmakers, Eric-Jan: Quantifying uncertainty in transdimensional Markov chain Monte Carlo using discrete Markov models (2019)
  12. João Duarte; Vinícius Mayrink: slfm: An R Package to Evaluate Coherent Patterns in Microarray Data via Factor Analysis (2019) not zbMATH
  13. Kiefer, Nicholas; Oremek, Maximilian J.; Hoeft, Andreas; Zenker, Sven: Model-based quantification of left ventricular diastolic function in critically ill patients with atrial fibrillation from routine data: a feasibility study (2019)
  14. Cosme, Iria C. S.; Fernandes, Isaac F.; de Carvalho, João L.; Xavier-de-Souza, Samuel: Memory-usage advantageous block recursive matrix inverse (2018)
  15. Hartigan, Luke: Alternative HAC covariance matrix estimators with improved finite sample properties (2018)
  16. Huber, Andreas; Gerdts, Matthias; Bertolazzi, Enrico: Structure exploitation in an interior-point method for fully discretized, state constrained optimal control problems (2018)
  17. Jens Jakob Sørensen, Jesper Jensen, Till Heinzel, Jacob Sherson: QEngine: An open-source C++ Library for Quantum Optimal Control of Ultracold Atoms (2018) arXiv
  18. Leopoldo Catania; Nima Nonejad: Dynamic Model Averaging for Practitioners in Economics and Finance: The eDMA Package (2018) not zbMATH
  19. Sanderson, Conrad; Curtin, Ryan: A user-friendly hybrid sparse matrix class in C++ (2018)
  20. Shikhar Bhardwaj, Ryan R. Curtin, Marcus Edel, Yannis Mentekidis, Conrad Sanderson: ensmallen: a flexible C++ library for efficient function optimization (2018) arXiv

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