Financial Risk Management and Quantitative Analysis
R and C++ functions for financial risk management and
quantative analysis, using the generalized perbolic and its
related distributions.

The Generalized Hyperbolic Distribution, Related Distributions
and Their Applications in Finance
A collection of R and C++ functions to work with the
generalized hyperbolic distribution, related distributions and
their applications in financial risk management and
quantitative analysis.

Fast computation of moments via 'Rcpp'. Supports computation on
vectors and matrices, and Monoidal append of moments.

Fast, numerically robust computation of weighted moments via 'Rcpp'.
Supports computation on vectors and matrices, and Monoidal append of moments.
Moments and cumulants over running fixed length windows can be computed,
as well as over time-based windows.
Moment computations are via a generalization of Welford's method, as described
by Bennett et. (2009) <doi:10.1109/CLUSTR.2009.5289161>.
knitr, testthat, moments, PDQutils, e1071, microbenchmark

Tim Coelli <t.coelli@uq.edu.au>,
Arne Henningsen <arne.henningsen@googlemail.com>
Maximum Likelihood Estimation of
Stochastic Frontier Production and Cost Functions.
Two specifications are available:
the error components specification with time-varying efficiencies
(Battese and Coelli, 1992)
and a model specification in which the firm effects are directly
influenced by a number of variables (Battese and Coelli, 1995).

Maximum Likelihood Estimation of Stochastic Frontier
Production and Cost Functions. Two specifications are
available: the error components specification with time-varying
efficiencies (Battese and Coelli, 1992) and a model
specification in which the firm effects are directly influenced
by a number of variables (Battese and Coelli, 1995).

Maximum Likelihood Estimation of Stochastic Frontier
Production and Cost Functions.  Two specifications are
available: the error components specification with time-varying
efficiencies (Battese and Coelli, 1992) and a model
specification in which the firm effects are directly influenced
by a number of variables (Battese and Coelli, 1995).