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Linear Mixed-Effects Models using 'Eigen' and S4
Fit linear and generalized linear mixed-effects models. The models and their components are represented using S4 classes and methods. The core computational algorithms are implemented using the 'Eigen' C++ library for numerical linear algebra and 'RcppEigen' "glue".
Interface R to MPFR - Multiple Precision Floating-Point Reliable
Arithmetic (via S4 classes and methods) for arbitrary precision floating point numbers, including transcendental ("special") functions. To this end, the package interfaces to the 'LGPL' licensed 'MPFR' (Multiple Precision Floating-Point Reliable) Library which itself is based on the 'GMP' (GNU Multiple Precision) Library.
Modelling with Sparse and Dense Matrices
Generalized Linear Modelling with sparse and dense 'Matrix' matrices, using modular prediction and response module classes.
Rmetrics - Chronological and Calendar Objects
The 'timeDate' class fulfils the conventions of the ISO 8601 standard as well as of the ANSI C and POSIX standards. Beyond these standards it provides the "Financial Center" concept which allows to handle data records collected in different time zones and mix them up to have always the proper time stamps with respect to your personal financial center, or alternatively to the GMT reference time. It can thus also handle time stamps from historical data records from the same time zone, even if the financial centers changed day light saving times at different calendar dates.
Statistics for Long-Memory Processes (Book Jan Beran), and Related Functionality
Datasets and Functionality from 'Jan Beran' (1994). Statistics for Long-Memory Processes; Chapman & Hall. Estimation of Hurst (and more) parameters for fractional Gaussian noise, 'fARIMA' and 'FEXP' models.
Financial Time Series Objects (Rmetrics)
'S4' classes and various tools for financial time series: Basic functions such as scaling and sorting, subsetting, mathematical operations and statistical functions.
Quantile Regression
Estimation and inference methods for models for conditional quantile functions:
Linear and nonlinear parametric and non-parametric (total variation penalized) models
for conditional quantiles of a univariate response and several methods for handling
censored survival data. Portfolio selection methods based on expected shortfall
risk are also now included. See Koenker, R. (2005) Quantile Regression, Cambridge U. Press,
Sparse Linear Algebra
Some basic linear algebra functionality for sparse matrices is provided: including Cholesky decomposition and backsolving as well as standard R subsetting and Kronecker products.
Embedded Conic Solver in R
R interface to the Embedded COnic Solver (ECOS), an efficient and robust C library for convex problems. Conic and equality constraints can be specified in addition to integer and boolean variable constraints for mixed-integer problems. This R interface is inspired by the python interface and has similar calling conventions.
Rmetrics - Markets and Basic Statistics
Provides a collection of functions to explore and to investigate basic properties of financial returns and related quantities. The covered fields include techniques of explorative data analysis and the investigation of distributional properties, including parameter estimation and hypothesis testing. Even more there are several utility functions for data handling and management.