c(person("Marta", "Nai Ruscone", role = c("aut", "cre"),
email = "mnairuscone@liuc.it"),
person("Laura", "Deldossi", role = c("aut")),
person("Cleve", "Moler", role = "ctb",
comment = "LINPACK routines in src"),
person("Jack", "Dongarra", role = "ctb",
comment = "LINPACK routines in src"))
Marta Nai Ruscone [aut, cre],
Laura Deldossi [aut],
Cleve Moler [ctb] (LINPACK routines in src),
Jack Dongarra [ctb] (LINPACK routines in src)

c(person("Marta", "Nai Ruscone", role = c("aut", "cre"),
email = "marta.nairuscone@unige.it"),
person("Laura", "Deldossi", role = c("aut")),
person("Cleve", "Moler", role = "ctb",
comment = "LINPACK routines in src"),
person("Jack", "Dongarra", role = "ctb",
comment = "LINPACK routines in src"))
Implements the objective Bayesian methodology proposed in Consonni and Deldossi in order to choose the optimal experiment that better discriminate between competing models, see Deldossi and Nai Ruscone (2020) <doi:10.18637/jss.v094.i02>.

Computes optimal capital allocations based on some standard principles such as Haircut, Overbeck type II and the Covariance Allocation Principle. It also provides some shortcuts for obtaining the Value at Risk and the Expectation Shortfall, using both the normal and the t-student distribution, see Urbina and Guillén (2014)<doi:10.1016/j.eswa.2014.05.017> and Urbina (2013)<http://hdl.handle.net/2099.1/19443>.

c(person(given = "Luca",
family = "Carraro",
role = c("aut", "cre"),
email = "luca.carraro@hotmail.it"),
person(given = "Florian",
family = "Altermatt",
role = "ctb"),
person(given = "Emanuel A.",
family = "Fronhofer",
role = "ctb"),
person(given = "Reinhard",
family = "Furrer",
role = "ctb"),
person(given = "Isabelle",
family = "Gounand",
role = "ctb"),
person(given = "Andrea",
family = "Rinaldo",
role = "ctb"),
person(given = "Enrico",
family = "Bertuzzo",
role = "aut"))
Generate and analyze Optimal Channel Networks (OCNs):
oriented spanning trees reproducing all scaling features characteristic
of real, natural river networks. As such, they can be used in a variety
of numerical experiments in the fields of hydrology, ecology and
epidemiology. See Rinaldo et al. (2014) <doi:10.1073/pnas.1322700111>
for an overview on the OCN concept; Furrer and Sain (2010)
<doi:10.18637/jss.v036.i10> for the construct used.
fields, spam, rgl, methods, igraph, SSN, rgdal, sp
Luca Carraro [aut, cre],
Florian Altermatt [ctb],
Emanuel A. Fronhofer [ctb],
Reinhard Furrer [ctb],
Isabelle Gounand [ctb],
Andrea Rinaldo [ctb],
Enrico Bertuzzo [aut]