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Journal of Statistical Software, Volume 109
Volume 109, Number 1, 2024
- John M. Niehaus, Lin Zhu, Scott J. Cook, Mikyoung Jun:
bizicount: Bivariate Zero-Inflated Count Copula Regression Using R.
Volume 109, Number 2, 2024
- Carlos Ramos-Carreño, José Luis Torrecilla, Miguel Carbajo-Berrocal, Pablo Marcos, Alberto Suárez:
scikit-fda: A Python Package for Functional Data Analysis.
Volume 109, Number 3, 2024
- Pavlin G. Policar, Martin Strazar, Blaz Zupan:
openTSNE: A Modular Python Library for t-SNE Dimensionality Reduction and Embedding.
Volume 109, Number 4, 2024
- Samuel W. K. Wong, Shihao Yang, S. C. Kou:
magi: A Package for Inference of Dynamic Systems from Noisy and Sparse Data via Manifold-Constrained Gaussian Processes.
Volume 109, Number 5, 2024
- José Betancourt, François Bachoc, Thierry Klein, Déborah Idier, Jérémy Rohmer, Yves Deville:
funGp: An R Package for Gaussian Process Regression with Scalar and Functional Inputs.
Volume 109, Number 6, 2024
- Jonathan Jalbert, Marilou Farmer, Gabriel Gobeil, Philippe Roy:
Extremes.jl: Extreme Value Analysis in Julia.
Volume 109, Number 7, 2024
- Paul Fearnhead, Daniel Grose:
cpop: Detecting Changes in Piecewise-Linear Signals.
Volume 109, Number 8, 2024
- Robin K. S. Hankin:
Generalized Plackett-Luce Likelihoods.
Volume 109, Number 9, 2024
- Lennart Oelschläger, Timo Adam, Rouven Michels:
fHMM: Hidden Markov Models for Financial Time Series in R.
Volume 109, Number 10, 2024
- Andrew Iskauskas, Ian R. Vernon, Michael Goldstein, Danny Scarponi, Nicky McCreesh, Trevelyan J. McKinley, Richard G. White:
Emulation and History Matching Using the hmer Package.
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