Pot Package. InstallationExamplesAcknowledgementsContributions and Code of ConductSupportReferencesThe library has been tested on Linux MacOSX and Windows It requires a C++ compiler for building/installing the EMD solver and relies on the following Python modules 1 Numpy (>=116) 2 Scipy (>=10) 3 Cython (>=023) (build only not necessary when installing from pip or conda) Short examples 1 Import the toolbox 1 Compute Wasserstein distances 1 Compute OT matrix 1 Compute Wasserstein barycenter Examples and Notebooks The examples folder contain several examples and use case for the library The full documentation with examples and output is available on https//PythonOTgithubio/ This toolbox has been created and is maintained by 1 Rémi Flamary 2 Nicolas Courty The contributors to this library are 1 Alexandre Gramfort(CI documentation) 2 Laetitia Chapel(Partial OT) 3 Michael Perrot(Mapping estimation) 4 Léo Gautheron(GPU implementation) 5 Nathalie Gayraud(DA classes) 6 Stanislas Chambon(DA classes) 7 Antoine Rolet(EMD solver debug) 8 Erwan Vautier (GromovWasserstein) 9 Kilian Fatras(Stochastic solvers) 10 Alain Rakotomamonjy 11 Vayer Titouan(GromovWasserstein FusedGromovWasserstein) 12 Hicham Janati(Unbalanced OT Debiased barycenters) 13 Romain Tavenard(1d Wasserstein) 14 Mokhtar Z Alaya(Screenkhorn) 15 Ievgen Redko(Laplacian DA JCPOT) 16 Adrien Corenflos(Sliced Wasserstein Distance) 17 Tanguy Kerdoncuff(Sampled Gromov Wasserstein) 18 Minhui Huang(Projection Robust Wasserstein Distance) 19 Nathan Cassereau(Backends) This toolbox benefit a lot from open source research and we would like to thank the following persons for provid Every contribution is welcome and should respect the contribution guidelines Each member of the project is expected to follow the code of conduct You can ask questions and join the development discussion 1 On the POT slack channel 2 On the POT gitter channel 3 On the POT mailing list You can also post bug reports and feature requests in Github issues Make sure to read our guidelinesfirst Bonneel N Van De Panne M Paris S & Heidrich W (2011 December) Displacement interpolation using Lagrangian mass transport In ACM Transactions on Graphics (TOG) (Vol 30 No 6 p 158) ACM Cuturi M (2013) Sinkhorn distances Lightspeed computation of optimal transport In Advances in Neural Information Processing Systems (pp 22922300) Benamou J D Carlier G Cuturi M Nenna L & Peyré G (2015) Iterative Bregman projections for regularized transportation problems SIAM Journal on Scientific Computing 37(2) A1111A1138 S Nakhostin N Courty R Flamary D Tuia T Corpetti Supervised planetary unmixing with optimal transport Whorkshop on Hyperspectral Image and Signal Processing Evolution in Remote Sensing (WHISPERS) 2016 N Courty R Flamary D Tuia A Rakotomamonjy Optimal Transport for Domain Adaptation in IEEE Transactions on Pattern Analysis and Machine Intelligence volPP no99 pp11 Ferradans S Papadakis N Peyré G.
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POT package RDocumentation
internals Internal functions and methods for the POT package lmomplot Threshold Selection The Lmoments Plot logLikpot Extract LogLikelihood mrlplot Threshold Selection The Empirical Mean Residual Life Plot pickDep The Pickands' Dependence Function plotbvpot Graphical Diagnostics the Bivariate Extreme Value License GPL (>= 2)Version 117.
The POT Package: An R package to model peaks over threshold
Internal functions and methods for the POT package plotbvpot Graphical Diagnostics the Bivariate Extreme Value Distribution Model ts2tsd Mobile Window on a Time Series lmomplot Threshold Selection The Lmoments Plot plotmcpot Graphical Diagnostics Markov Chains for All Exceedances.
POT: Generalized Pareto Distribution and Peaks Over Threshold
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The POT package aims to provide operational tools to analyze POT This package relies on the EVT to model the tail of any continuous distribution Tail modelling in particular POT modelling is of great importance for many financial and environmental applications The POT package was first committed to the CRAN in April 2005 and is still in active developmentThe main motivation was to provide practical tools for probabilistic modelling of high flood flows The project consists in developing functions for peaks over The project consists in developing functions for peaks over Email Address * This email address will be verified before 11 Why the POT package? The POT package is an addon.