BayesMallowsSMC2: Nested Sequential Monte Carlo for the Bayesian Mallows Model
This R package provides nested sequential Monte Carlo algorithms for performing sequential inference in the Bayesian Mallows model.
Multilevel Semiparametric Latent Variable Modeling in R with "galamm"
This paper presents the R package "galamm", which contains open-source implementations for generalized additive latent and mixed models (GALAMMs). Published in Multivariate Behavioral Research.
galamm - Generalized Additive Latent and Mixed Models
This R package contains functions for estimating generalized additive latent and mixed models.
BayesianLaterality - Predict Brain Asymmetry Based on Handedness and Dichotic Listening
This R package contains functions for estimating whether a subject is left- or right-dominant for language processing based on the results of dichotic listening experiments and information about handedness.
BayesMallows: An R Package for the Bayesian Mallows Model
This paper presents the BayesMallows R package, for analysis of rank and preference data. Published in the R Journal.
metagam: Meta-Analysis of Generalized Additive Models
This R package contains functions for meta analysis using generalized additive (mixed) models, by combining fits from multiple studies.
hdme: High-Dimensional Regression with Measurement Error
This paper presents the hdme package, implementing variable selection methods for regression with covariate measurement error.
BayesMallows: Bayesian Preference Learning with the Mallows Rank Model
This R package contains functions for estimating the Bayesian Mallows model in a wide range of situation, using the Metropolis-Hastings algorithm.
hdme: High-Dimensional Regression with Measurement Error
This R package contains functions for fitting variable selection models in the presence of noise in the predictor variables. In particular, it supports a corrected lasso and the generalized matrix uncertainty selector. In addition, it offers an implementation of the (generalized) Dantzig selector.