## Installing from CRAN install.packages("foo") ## Installing from R-Forge install.packages("foo", repos = "http://R-Forge.R-project.org") ## Installing from GitHub library(devtools) install_github("bpfaff/foo")
Routines for solving convex optimization problems with cone constraints by means of interior-point methods. The implemented algorithms are partially ported from CVXOPT, a Python module for convex optimization (see http://cvxopt.org for more information).
Functions for extreme value theory, which may be divided into the following groups:
Accompanying package of the book Financial Risk Modelling and Portfolio Optimisation with R, second edition, 2018, John Wiley & Sons. The data sets used in the book are contained in this package.
Implementation of the GO-GARCH model class.
Multiple criteria risk parity optimization with respect to higher moments.
Accompanying package to the book Quantitative Risk Management: Concepts, Techniques and Tools, first edition by Alexander J. McNeil, Rüdiger Frey, and Paul Embrechts.2
Implementation of the RPC-JSON API for Bitcoin and utility functions for address creation and content analysis of the blockchain.
Implementation of the the XML-RPC API to NEOS. This enables the user to pass optimization problems to NEOS and retrieve results within R.
Unit root and cointegration tests encountered in applied econometric analysis are implemented (accompanying package to the book Analysis of Integrated and Cointegrated Time Series with R).
Estimation, lag selection, diagnostic testing, forecasting, causality analysis, forecast error variance decomposition and impulse response functions of VAR models and estimation of SVAR and SVEC models (accompanying package to the book Analysis of Integrated and Cointegrated Time Series with R).