%% Bibliography for R package

@article{GuthrieFranck2024,
	author = {Adeline P. Guthrie and Christopher T. Franck},
	title = {Boldness-Recalibration for Binary Event Predictions},
	journal = {The American Statistician},
	volume = {0},
	number = {0},
	pages = {1--11},
	year = {2024},
	publisher = {Taylor \& Francis},
	doi = {10.1080/00031305.2024.2339266},
	URL = {https://doi.org/10.1080/00031305.2024.2339266},
	eprint = { https://doi.org/10.1080/00031305.2024.2339266}
}



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%                      Data sets                       %
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@dataset{fivethirtyeight,
  	author = {FiveThirtyEight},
  	title = {2020-21 NHL Predictions},
  	year = {2021},
  	publisher = {fivethirtyeight.com},
  	url = {https://data.fivethirtyeight.com/},
  	urldate = {2022-11-08},
  	note = {Accessed: 2022-01-05}
}

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%                    Algorithms                        %
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@article{auglag1,
	author = {Conn, Andrew R. and Gould, Nicholas I. M. and Toint, Philippe L.},
	title = {A globally convergent augmented Lagrangian algorithm for optimization with general constraints and simple bounds},
	year = {1991},
	issue_date = {April 1991},
	publisher = {Society for Industrial and Applied Mathematics},
	address = {USA},
	volume = {28},
	number = {2},
	issn = {0036-1429},
	url = {https://doi.org/10.1137/0728030},
	doi = {10.1137/0728030},
	journal = {SIAM J. Numer. Anal.},
	month = {feb},
	pages = {545–572},
	numpages = {28}
}

@article{auglag2,
  	title={Improving ultimate convergence of an augmented Lagrangian method},
	author={Ernesto G. Birgin and Jos{\'e} Mario Mart{\'i}nez},
  	journal={Optimization Methods and Software},
  	year={2008},
  	volume={23},
  	pages={177 - 195},
  	url={https://doi.org/10.1080/10556780701577730}
}

@article{MMA,
	author = {Svanberg, Krister},
	year = {2002},
	month = {01},
	pages = {555-573},
	title = {A Class of Globally Convergent Optimization Methods Based on Conservative Convex Separable Approximations},
	volume = {12},
	journal = {SIAM Journal on Optimization},
	doi = {10.1137/S1052623499362822}
}

@article{nelder-mead,
    	author = {Nelder, J. A. and Mead, R.},
    	title = "{A Simplex Method for Function Minimization}",
    	journal = {The Computer Journal},
    	volume = {7},
    	number = {4},
    	pages = {308-313},
    	year = {1965},
    	month = {01},
    	abstract = "{A method is described for the minimization of a function of n variables, which depends on the comparison of function values at the (n + 1) vertices of a general simplex, followed by the replacement of the vertex with the highest value by another point. The simplex adapts itself to the local landscape, and contracts on to the final minimum. The method is shown to be effective and computationally compact. A procedure is given for the estimation of the Hessian matrix in the neighbourhood of the minimum, needed in statistical estimation problems.}",
    	issn = {0010-4620},
    	doi = {10.1093/comjnl/7.4.308},
    	url = {https://doi.org/10.1093/comjnl/7.4.308},
    	eprint = {https://academic.oup.com/comjnl/article-pdf/7/4/308/1013182/7-4-308.pdf},
}

@book{slsqp1,
  	title={A Software Package for Sequential Quadratic Programming},
  	author={Kraft, Dieter},
  	series={Deutsche Forschungs- und Versuchsanstalt f{\"u}r Luft- und Raumfahrt K{\"o}ln: Forschungsbericht},
  	url={https://books.google.com/books?id=4rKaGwAACAAJ},
  	year={1988},
  	publisher={Wiss. Berichtswesen d. DFVLR}
}

@article{slsqp2,
	author = {Kraft, Dieter},
	title = {Algorithm 733: TOMP–Fortran modules for optimal control calculations},
	year = {1994},
	issue_date = {Sept. 1994},
	publisher = {Association for Computing Machinery},
	address = {New York, NY, USA},
	volume = {20},
	number = {3},
	issn = {0098-3500},
	url = {https://doi.org/10.1145/192115.192124},
	doi = {10.1145/192115.192124},
	abstract = {A great number of analysis and synthesis problems of modern processes can be written as state and control constrained optimal control problems governed by ordinary differential equations with multipoint boundary values. As the software tools for following this attractive approach are still missing or can be used only by experts, the structure and usage of an easy-to-use software package is described which efficiently solves the given problem. Among its features are user-orientation, applicability on personal computers and mainframes, and robustness with respect to model changes and inaccurate starting values. It has been tested on a number of complex engineering tasks, including aerospace and robotic trajectory planning.},
	journal = {ACM Trans. Math. Softw.},
	month = {sep},
	pages = {262–281},
	numpages = {20},
	keywords = {shooting method, robotics, optimal control, manipulators, boundary value problems}
}

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%                        R packages                    %
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@misc{nloptr-package,
  	title = {The {NLopt} nonlinear-optimization package},
  	author = {Steven G. Johnson},
  	year = {2007},
  	howpublished = {\url{https://github.com/stevengj/nlopt}}
}