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Journal of Statistical Software, Volume 111
Volume 111, Number 1, 2024
- Benedikt B. Claus, Julia Wager, Udo Bonnet:
clinicalsignificance: Clinical Significance Analyses of Intervention Studies in R.
Volume 111, Number 2, 2024
- Mads Lindskou, Torben Tvedebrink, Poul Svante Eriksen, Søren Højsgaard, Niels Morling:
jti and sparta: Time and Space Efficient Packages for Model-Based Prediction in Large Bayesian Networks.
Volume 111, Number 3, 2024
- Mari Myllymäki, Tomás Mrkvicka:
GET: Global Envelopes in R.
Volume 111, Number 4, 2024
- Markus J. Fülle, Alexander Lange, Christian M. Hafner, Helmut Herwartz:
BEKKs: An R Package for Estimation of Conditional Volatility of Multivariate Time Series.
Volume 111, Number 5, 2024
- Sophie Hautphenne, Brendan Patch:
Birth-and-Death Processes in Python: The BirDePy Package.
Volume 111, Number 6, 2024
- Sheng Dai, Yu-Hsueh Fang, Chia-Yen Lee, Timo Kuosmanen:
pyStoNED: A Python Package for Convex Regression and Frontier Estimation.
Volume 111, Number 7, 2024
- Patrick Schratz, Marc Becker, Michel Lang, Alexander Brenning:
mlr3spatiotempcv: Spatiotemporal Resampling Methods for Machine Learning in R.
Volume 111, Number 8, 2024
- Niklas Koenen, Marvin N. Wright:
Interpreting Deep Neural Networks with the Package innsight.
Volume 111, Number 9, 2024
- Vincent Arel-Bundock, Noah Greifer, Andrew Heiss:
How to Interpret Statistical Models Using marginaleffects for R and Python.
Volume 111, Number 10, 2024
- Lucas Kook, Philipp F. M. Baumann, Oliver Dürr, Beate Sick, David Rügamer:
Estimating Conditional Distributions with Neural Networks Using R Package deeptrafo.
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