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Cannon A (2024). qrnn: Quantile Regression Neural Network. R package version 2.1.1, https://CRAN.R-project.org/package=qrnn.
Cannon AJ (2011). “Quantile regression neural networks: implementation in R and application to precipitation downscaling.” Computers & Geosciences, 37, 1277-1284. doi:10.1007/b98882.
Cannon AJ (2018). “Non-crossing nonlinear regression quantiles by monotone composite quantile regression neural network, with application to rainfall extremes.” Stochastic Environmental Research and Risk Assessment, 32(11), 3207-3225. doi:10.1007/s00477-018-1573-6.
Corresponding BibTeX entries:
@Manual{,
title = {qrnn: Quantile Regression Neural Network},
author = {Alex J. Cannon},
year = {2024},
note = {R package version 2.1.1},
url = {https://CRAN.R-project.org/package=qrnn},
}
@Article{,
title = {Quantile regression neural networks: implementation in R
and application to precipitation downscaling},
author = {Alex J. Cannon},
year = {2011},
journal = {Computers \& Geosciences},
volume = {37},
pages = {1277-1284},
doi = {10.1007/b98882},
}
@Article{,
title = {Non-crossing nonlinear regression quantiles by monotone
composite quantile regression neural network, with application to
rainfall extremes},
author = {Alex J. Cannon},
year = {2018},
journal = {Stochastic Environmental Research and Risk Assessment},
volume = {32(11)},
pages = {3207-3225},
doi = {10.1007/s00477-018-1573-6},
}
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