
DPpackage
 Referenced in 62 articles
[sw10495]
 DPpackage: Bayesian Semi and Nonparametric Modeling in R. Data analysis sometimes requires the relaxation ... specification of the probability model. In the Bayesian context, this is accomplished by placing ... programs for the implementation of some Bayesian nonparametric and semiparametric models in R, DPpackage. Currently...

BayesTree
 Referenced in 58 articles
[sw07995]
 posterior. Effectively, BART is a nonparametric Bayesian regression approach which uses dimensionally adaptive random basis...

bnpmr
 Referenced in 19 articles
[sw11018]
 Bayesian monotonic nonparametric regression. Implements the Bayesian nonparametric monotonic regression method described in Bornkamp & Ickstadt...

spBayesSurv
 Referenced in 7 articles
[sw16371]
 models for spatial/nonspatial survival data: marginal Bayesian Nonparametric models, marginal Bayesian proportional hazards models, generalized...

beyondWhittle
 Referenced in 6 articles
[sw31734]
 Stationary Time Series. Implementations of Bayesian parametric, nonparametric and semiparametric procedures for univariate and multivariate...

dpmixsim
 Referenced in 3 articles
[sw24713]
 segmentation. The DPM model is a Bayesian nonparametric methodology that relies on MCMC simulations...

phylodyn
 Referenced in 3 articles
[sw19813]
 genealogies. The package main functionality is Bayesian nonparametric estimation of effective population size fluctuations over...

dirichletprocess
 Referenced in 2 articles
[sw32614]
 Process Objects for Bayesian Modelling. Perform nonparametric Bayesian analysis using Dirichlet processes without the need...

Bayesian Regression
 Referenced in 2 articles
[sw19268]
 menudriven software package of Bayesian nonparametric (and parametric) mixed models for regression analysis...

ConfBands
 Referenced in 29 articles
[sw12330]
 methods: (a) as a standard (fixed effect) nonparametric model, (b) using the mixedmodel framework ... random effects, and (c) a full Bayesian approach. The volumeoftube formula is applied...

msBP
 Referenced in 2 articles
[sw23268]
 Multiscale Bernstein Polynomials for Densities. Performs Bayesian nonparametric multiscale density estimation and multiscale testing...

BNPmix
 Referenced in 2 articles
[sw28208]
 process mixture models are flexible Bayesian nonparametric models to deal with density estimation. Estimation could...

BNPMIXcluster
 Referenced in 1 article
[sw18028]
 package BNPMIXcluster. Bayesian Nonparametric Model for Clustering with Mixed Scale Variables. Bayesian nonparametric approach...

MixedDataImpute
 Referenced in 1 article
[sw18615]
 Continuous and Categorical Data using Nonparametric Bayesian Joint Models. Missing data imputation for continuous ... categorical data, using nonparametric Bayesian joint models (specifically the hierarchically coupled mixture model with local...

GLFM
 Referenced in 1 article
[sw35679]
 this paper, we introduce a general Bayesian nonparametric latent feature allocation model suitable for heterogeneous ... attributes per MCMC iteration. Second, the Bayesian nonparametric component allows us to place a prior...

bsplinePsd
 Referenced in 1 article
[sw31798]
 package bsplinePsd: Bayesian Nonparametric Spectral Density Estimation Using BSpline Priors. Implementation of a Metropolis...

ParticleMDI
 Referenced in 1 article
[sw35255]
 subtype identification. We present a novel nonparametric Bayesian approach for performing cluster analysis...

CSI
 Referenced in 1 article
[sw13904]
 nonparametric Bayesian approach to network inference from multiple perturbed time series gene expression data. Here...

BayClone2
 Referenced in 1 article
[sw31387]
 data, we characterize tumor heterogeneity using Bayesian nonparametric inference. Specifically, we estimate the number...

MOTABAR
 Referenced in 2 articles
[sw12739]
 Moving Taylor Bayesian regression for nonparametric multidimensional function estimation with possibly correlated errors. We study ... novel nonparametric method for estimating the value and several derivatives of an unknown, sufficiently smooth ... correlation structure. The method, moving Taylor Bayesian regression (MOTABAR), uses Bayesian updating to find...