No-U-Turn MCMC Sampling for ‘ADMB’ and ‘TMB’ Models (adnuts)
Bayesian inference using the no-U-turn (NUTS) algorithm by Hoffman and Gelman (2014) <http://…/hoffman14a.html>. Designed for ‘AD Model Builder’ (‘ADMB’) models, or when R functions for log-density and log-density gradient are available, such as ‘Template Model Builder’ (‘TMB’) models and other special cases. Functionality is similar to ‘Stan’, and the ‘rstan’ and ‘shinystan’ packages are used for diagnostics and inference.

Recovering a Basic Space from Issue Scales (basicspace)
Conducts Aldrich-McKelvey and Blackbox Scaling (Poole et al 2016) <doi:10.18637/jss.v069.i07> to recover latent dimensions of judgment.

Object-Oriented Implementation of CRM Designs (crmPack)
Implements a wide range of model-based dose escalation designs, ranging from classical and modern continual reassessment methods (CRMs) based on dose-limiting toxicity endpoints to dual-endpoint designs taking into account a biomarker/efficacy outcome. The focus is on Bayesian inference, making it very easy to setup a new design with its own JAGS code. However, it is also possible to implement 3+3 designs for comparison or models with non-Bayesian estimation. The whole package is written in a modular form in the S4 class system, making it very flexible for adaptation to new models, escalation or stopping rules.

Logit Leaf Model Classifier for Binary Classification (LLM)
Fits the Logit Leaf Model, makes predictions and visualizes the output. (De Caigny et al., (2018) <DOI:10.1016/j.ejor.2018.02.009>).

Mixed-Frequency GARCH Models (mfGARCH)
Estimating GARCH-MIDAS (MIxed-DAta-Sampling) models (Engle, Ghysels, Sohn, 2013, <doi:10.1162/REST_a_00300>) and related statistical inference, accompanying the paper ‘Two are better than one: volatility forecasting using multiplicative component GARCH models’ by Conrad, Kleen (2018, Working Paper). The GARCH-MIDAS model decomposes the conditional variance of (daily) stock returns into a short- and long-term component, where the latter may depend on an exogenous covariate sampled at a lower frequency.