Cannon A (2023).

qrnn: Quantile Regression Neural Network. R package version 2.1, 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 = {2023}, note = {R package version 2.1}, 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}, }