Ott Toomet <otoomet@ut.ee>,
Arne Henningsen <arne.henningsen@googlemail.com>,
with contributions from Spencer Graves

Ott Toomet <otoomet@ut.ee>, Arne Henningsen
<arne.henningsen@googlemail.com>, with contributions from
Spencer Graves

Ott Toomet <otoomet@ut.ee>,
Arne Henningsen <ahenningsen@agric-econ.uni-kiel.de>

Ott Toomet <otoomet@ut.ee>,
Arne Henningsen <ahenningsen@agric-econ.uni-kiel.de>,
with contributions from Spencer Graves

Ott Toomet <otoomet@ut.ee>, Arne Henningsen
<arne.henningsen@googlemail.com>, with contributions from
Spencer Graves and Yves Croissant

Ott Toomet <otoomet@gmail.com>, Arne Henningsen
<arne.henningsen@googlemail.com>, with contributions from
Spencer Graves and Yves Croissant

Ott Toomet <otoomet@gmail.com>,
Arne Henningsen <arne.henningsen@gmail.com>,
with contributions from Spencer Graves and Yves Croissant

Maximum Likelihood Estimation and Related Tools
Functions for Maximum Likelihood (ML) estimation and non-linear
optimization, and related tools.  It includes a unified way to call
different optimizers, and classes and methods to handle the results from
the ML viewpoint.  It also includes a number of convenience tools for testing
and developing your own models.

Functions for Maximum Likelihood (ML) estimation, non-linear
optimization, and related tools.  It includes a unified way to call
different optimizers, and classes and methods to handle the results from
the Maximum Likelihood viewpoint.  It also includes a number of convenience tools for testing
and developing your own models.

c(person("Ott", "Toomet", role=c("aut", "cre"), email="otoomet@gmail.com"),
person("Arne", "Henningsen", role=c("aut"), email="arne.henningsen@gmail.com"),
person("Spencer", "Graves", role=c("ctb")),
person("Yves", "Croissant", role=c("ctb")),
person("David", "Hugh-Jones", role=c("ctb")),
person("Luca", "Scrucca", role=c("ctb"))
)
MASS, clue, dlm, plot3D, tibble, tinytest
Functions for Maximum Likelihood (ML) estimation, non-linear
optimization, and related tools.  It includes a unified way to call
different optimizers, and classes and methods to handle the results from
the Maximum Likelihood viewpoint.  It also includes a number of convenience
tools for testing and developing your own models.
Ott Toomet [aut, cre],
Arne Henningsen [aut],
Spencer Graves [ctb],
Yves Croissant [ctb],
David Hugh-Jones [ctb],
Luca Scrucca [ctb]