Ioannis Kosmidis | (author, maintainer) |
---|---|
Nicola Lunardon | (author) |
GEEBRA is a Julia package that implements M
-estimation for
statistical models, either by solving estimating equations or by
maximizing inference objectives, like
likelihoods and
composite likelihoods (see, Varin et al,
2011,
for a review), using user-specified templates of the estimating
function or the objective functions contributions.
A key feature is the use of only those templates and forward mode
automatic differentiation (as implemented in
ForwardDiff) to
provide methods for reduced-bias M
-estimation
(RBM
-estimation; see, Kosmidis & Lunardon, 2020). RBM
-estimation takes place either through the
adjustment of the estimating equations or the penalization of the
objectives, or the subtraction of an estimate of the bias of the
M
-estimator from the M
-estimates.
See the examples for a showcase of the functionaly GEEBRA provides.
See NEWS.md for changes, bug fixes and enhancements.
GEEBRA has been designed so that the only requirements from the user are to:
- implement a Julia composite type for the data;
- implement a function for computing the number of observations from the data object;
- implement a function for calculating the contribution to the estimating function or to the objective function from a single observation that has arguments the parameter vector, the data object, and the observation index;
- specify a GEEBRA template (using
estimating_function_template
for estimating functions andobjective_function_template
for objective function) that has fields the functions for computing the contributions to the estimating functions or to the objective, and the number of observations.
GEEBRA, then, can estimate the unknown parameters by either
M
-estimation or RBM
-estimation.
Pages = [
"man/examples.md",
]
Pages = [
"lib/public.md",
"lib/internal.md",
]
Pages = [
"lib/public.md",
"lib/internal.md",
]