references.bib

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% Non-Life Insurance
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@Manual{italian-civil-code,
    title = {Codice Civile},
    author = {Stato Italiano},
    year = {2020},
    url = {https://www.brocardi.it/codice-civile/}
}

@book{ania-claim-freq,
    author = {ANIA},
    title = {Yearly statistical report for motor third party liability in Italy},
    month = "November",
    year = "2019",
    url = {https://www.ania.it/ricerca-avanzata/-/asset_publisher/XIyLeujL9irt/content/id/113283}
}

@book{iaa-about-actuaries,
    title = {About Actuaries},
    author = {International Actuarial Association (IAA)},
    year = {2021},
    url = {https://www.actuaries.org/iaa/IAA/About_the_IAA/About_Actuaries/About%20Actuaries.aspx}
}



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% Theoretical articles and books
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@book{wuthrich-non-life-insurance-math-stats,
    title = {Non-Life Insurance: Mathematics \& Statistics},
    author = {M. V. Wüthrich},
    month = {December},
    year = {2020},
    publisher = {ETH Zurich},
    url = {https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2319328}
}

@book{wuthrich-data-analytics,
    title = {Data Analytics for Non-Life Insurance Pricing},
    author = {M. V. Wüthrich},
    month = {September},
    year = {2020},
    publisher = {ETH Zurich},
    url = {https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2870308}
}

@book{gigante2010tariffazione,
    title = {La tariffazione nei rami danni con modelli lineari generalizzati},
    author = {Gigante, Patrizia and Picech, Liviana and Sigalotti, Luciano},
    year = {2010},
    publisher = {EUT Edizioni Universit{\`a} di Trieste},
    url = {https://www.libreriauniversitaria.it/tariffazione-rami-danni-modelli-lineari/libro/9788883032837}
}

@book{azzalini1996statistical,
  title = {Statistical inference based on the likelihood},
  author = {Azzalini, Adelchi},
  volume = {68},
  year = {1996},
  publisher = {CRC Press}
}

@book{sica-2016,
    title = {Analisi sull'Utilizzo di Variabili Telematiche nella Tariffazione delle Assicurazioni RCA},
    author = {Sica, Leonardo and Gigante, Patrizia},
    year = {2017},
    publisher = {Universit{\`a} degli Studi di Trieste}
}

@book{portugues-predictive-modeling,
    title = {Notes for Predictive Modeling},
    author = {Eduardo García Portugu{\'e}s},
    month = {December},
    year = {2020},
    publisher = {Carlos III University of Madrid},
    url = {https://bookdown.org/egarpor/PM-UC3M/}
}

@book{james2013introduction,
    title = {An introduction to statistical learning},
    author = {James, Gareth and Witten, Daniela and Hastie, Trevor and Tibshirani, Robert},
    volume = {112},
    year = {2013},
    publisher = {Springer},
    url = {https://www.statlearning.com/}
}

@book{friedman2001elements,
    title = {The elements of statistical learning},
    author = {Friedman, Jerome and Hastie, Trevor and Tibshirani, Robert and others},
    volume = {1},
    number = {10},
    year = {2001},
    publisher = {Springer series in statistics New York},
    url = {https://web.stanford.edu/~hastie/Papers/ESLII.pdf}
}

@book{davison2003statistical,
    title = {Statistical models},
    author = {Davison, Anthony Christopher},
    volume = {11},
    year = {2003},
    publisher = {Cambridge university press}
}

% Simpson's paradox
@article{blyth1972simpson,
    title = {On Simpson's paradox and the sure-thing principle},
    author = {Blyth, Colin R},
    journal = {Journal of the American Statistical Association},
    volume = {67},
    number = {338},
    pages = {364--366},
    year = {1972},
    publisher = {Taylor \& Francis},
    url = {https://www.jstor.org/stable/2284382?seq=1}
}

% Lidar dataset
@book{ruppert2003semiparametric,
    title = {Semiparametric regression},
    author = {Ruppert, David and Wand, Matt P and Carroll, Raymond J},
    number = {12},
    year = {2003},
    publisher = {Cambridge university press}
}

% Lidar dataset
@article{holst1996locally,
    title = {Locally weighted least squares kernel regression and statistical evaluation of LIDAR measurements},
    author = {Holst, Ulla and H{\"o}ssjer, Ola and Bj{\"o}rklund, Claes and Ragnarson, P{\"a}r and Edner, Hans},
    journal = {Environmetrics},
    volume = {7},
    number = {4},
    pages = {401--416},
    year = {1996},
    publisher = {Wiley Online Library}
}

% GAM
@book{wood2017generalized,
  title = {Generalized additive models: an introduction with R},
  author = {Wood, Simon N},
  year = {2017},
  publisher = {CRC press}
}

% Bayesian GLM
@book{gelman2013bayesian,
    title = {Bayesian data analysis},
    author = {Gelman, Andrew and Carlin, John B and Stern, Hal S and Dunson, David B and Vehtari, Aki and Rubin, Donald B},
    year = {2013},
    publisher = {CRC press}
}

@article{bayes-gam,
    author = {C. M. Crainiceanu, D. Ruppert, M. P. Wand},
    journal = {Journal of Statistical Software},
    title = {Bayesian Analysis for Penalized Spline Regression Using WinBUGS},
    year = {2005},
    url = {https://www.jstatsoft.org/article/view/v014i14}
}



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% R, Python, Spark and H2O manuals
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@Manual{r-manual,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2021},
    url = {https://www.R-project.org/}
}

@book{wickham2016r,
    title = {R for data science: import, tidy, transform, visualize, and model data},
    author = {Wickham, Hadley and Grolemund, Garrett},
    year = {2016},
    publisher = {" O'Reilly Media, Inc."},
    url = {https://r4ds.had.co.nz/}
}

@Manual{h2o_platform,
    title = {H2O: Scalable Machine Learning Platform},
    author = {H2O.ai},
    year = {2020},
    note = {version 3.30.0.6},
    url = {https://github.com/h2oai/h2o-3}
}

@Manual{h2o_R_booklet,
    title = {Machine Learning with R and H2O},
    author = {Landry, M.},
    year = {2020},
    month = {March},
    url = {http://docs.h2o.ai/h2o/latest-stable/h2o-docs/booklets/RBooklet.pdf}
}

@Manual{h2o_Python_booklet,
    title = {Machine Learning with Python and H2O},
    author = {Stetsenko, P.},
    year = {2020},
    month = {March},
    url = {http://docs.h2o.ai/h2o/latest-stable/h2o-docs/booklets/PythonBooklet.pdf}
}

@Manual{h2o_SW_booklet,
    title = {Machine Learning with Sparkling Water: H2O + Spark},
    author = {Malohlava, M., and Hava, J., and Mehta, N},
    year = {2020},
    month = {March},
    url = {http://docs.h2o.ai/h2o/latest-stable/h2o-docs/booklets/SparklingWaterBooklet.pdf}
}

@Manual{h2o_GLM_booklet,
    title = {Generalized Linear Modeling with H2O},
    author = {Nykodym, T. and Kraljevic, T. and Wang, A. and Wong W.},
    year = {2020},
    month = {March},
    url = {http://docs.h2o.ai/h2o/latest-stable/h2o-docs/booklets/GLMBooklet.pdf}
}

@Manual{h2o_GBM_booklet,
    title = {Gradient Boosting Machine with H2O},
    author = {Candel, A., and Malohlava, M.},
    year = {2020},
    month = {March},
    url = {http://docs.h2o.ai/h2o/latest-stable/h2o-docs/booklets/GBMBooklet.pdf}
}