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Local Polynomial (Ridge) Regression
Local Polynomial Regression with Ridging.
Bitmap Images / Pixel Maps
Functions for import, export, visualization and other manipulations of bitmapped images.
Rmetrics - Modeling of Multivariate Financial Return Distributions
A collection of functions inspired by Venables and Ripley (2002)
R Commander
A platform-independent basic-statistics GUI (graphical user interface) for R, based on the tcltk package.
Methods for Graphical Models and Causal Inference
Functions for causal structure learning and causal inference using graphical models. The main algorithms for causal structure learning are PC (for observational data without hidden variables), FCI and RFCI (for observational data with hidden variables), and GIES (for a mix of data from observational studies (i.e. observational data) and data from experiments involving interventions (i.e. interventional data) without hidden variables). For causal inference the IDA algorithm, the Generalized Backdoor Criterion (GBC), the Generalized Adjustment Criterion (GAC) and some related functions are implemented. Functions for incorporating background knowledge are provided.
Robust Statistics: Theory and Methods
Companion package for the book: "Robust Statistics: Theory and Methods, second edition", < http://www.wiley.com/go/maronna/robust>. This package contains code that implements the robust estimators discussed in the recent second edition of the book above, as well as the scripts reproducing all the examples in the book.
Examples from Multilevel Modelling Software Review
Data and examples from a multilevel modelling software review as well as other well-known data sets from the multilevel modelling literature.
Critical Line Algorithm in Pure R
Implements 'Markowitz' Critical Line Algorithm ('CLA') for classical
mean-variance portfolio optimization, see Markowitz (1952)
Variable Length Markov Chains ('VLMC') Models
Functions, Classes & Methods for estimation, prediction, and simulation (bootstrap) of Variable Length Markov Chain ('VLMC') Models.
Construct Graphs of S4 Class Hierarchies
Construct directed graphs of S4 class hierarchies and visualize them. In general, these graphs typically are DAGs (directed acyclic graphs), often simple trees in practice.