Computes the test statistic and p-value of the Cramer-von Mises and Anderson-Darling test for some continuous distribution functions proposed by Chen and Balakrishnan (1995) <http://asq.org/qic/display-item/index.html?item=11407>. In addition to our classic distribution functions here, we  calculate the Goodness of Fit (GoF) test to dataset which follows the extreme value distribution function, without remembering the formula of distribution/density functions. Calculates the Value at Risk (VaR) and Average VaR are another important risk factors which are estimated by using well-known distribution functions. Pflug and Romisch (2007, ISBN: 9812707409) is a good reference to study the properties of risk measures.

c(
person("Bruce", "Swihart", email="bruce.swihart@gmail.com", role=c("cre", "aut")),
person("Jim"  , "Lindsey", email="jlindsey@gen.unimaas.nl", role="aut", comment="Jim created this package, Bruce is maintaining the CRAN version")
)
A variety of functions to fit linear and nonlinear
regression with a large selection of distributions.

Functions to specify and fit generalized nonlinear models,
including models with multiplicative interaction terms such as
the UNIDIFF model from sociology and the AMMI model from crop
science, and many others.  Over-parameterized representations
of models are used throughout; functions are provided for
inference on estimable parameter combinations, as well as
standard methods for diagnostics etc.
MASS, stats, graphics, nnet, qvcalc (>= 0.8-3), relimp

Functions to specify and fit generalized nonlinear models, including models with multiplicative interaction terms such as the UNIDIFF model from sociology and the AMMI model from crop science.  This is a major re-working of an earlier Xlisp-Stat package, "Llama".  Over-parameterized representations of models are used throughout; functions are provided for inference on estimable parameter combinations, as well as standard methods for diagnostics etc.

Functions to specify and fit generalized nonlinear models, including models with multiplicative interaction terms such as the UNIDIFF model from sociology and the AMMI model from crop science, and many others.  Over-parameterized representations of models are used throughout; functions are provided for inference on estimable parameter combinations, as well as standard methods for diagnostics etc.