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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.
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,
Kernel Regression Smoothing with Local or Global Plug-in Bandwidth
Kernel regression smoothing with adaptive local or global plug-in bandwidth selection.
'eXtra' / 'eXperimental' Functionality for Robust Statistics
Robustness -- 'eXperimental', 'eXtraneous', or 'eXtraordinary'
Functionality for Robust Statistics. Hence methods which are not well established,
often related to methods in package 'robustbase'. Amazingly, 'BACON()', originally by
Billor, Hadi, and Velleman (2000)
Rmetrics - Autoregressive Conditional Heteroskedastic Modelling
Analyze and model heteroskedastic behavior in financial time series.
High-Dimensional Inference
Implementation of multiple approaches to perform inference in high-dimensional models.
Generalized Nonlinear Models
Functions to specify and fit generalized nonlinear models, including models with multiplicative interaction terms such as the UNIDIFF model from sociology and the AMMI model from crop science, and many others. Over-parameterized representations of models are used throughout; functions are provided for inference on estimable parameter combinations, as well as standard methods for diagnostics etc.
Bayesian Applied Regression Modeling via Stan
Estimates previously compiled regression models using the 'rstan' package, which provides the R interface to the Stan C++ library for Bayesian estimation. Users specify models via the customary R syntax with a formula and data.frame plus some additional arguments for priors.
DPQ (Density, Probability, Quantile) Distribution Computations using MPFR
An extension to the 'DPQ' package with computations for 'DPQ' (Density (pdf), Probability (cdf) and Quantile) functions, where the functions here partly use the 'Rmpfr' package and hence the underlying 'MPFR' and 'GMP' C libraries.
Local Polynomial (Ridge) Regression
Local Polynomial Regression with Ridging.