
CASPAR
 Referenced in 6 articles
[sw12242]
 CASPAR: a hierarchical bayesian approach to predict survival times in cancer from gene expression data ... that is embedded in a Bayesian framework. A hierarchical prior distribution on the regression parameters...

RSGHB
 Referenced in 5 articles
[sw23112]
 estimating models using a Hierarchical Bayesian (HB) framework. The flexibility comes in allowing the user ... Matlab and Gauss code for doing Hierarchical Bayesian estimation has served as the basis...

hBayesDM
 Referenced in 2 articles
[sw40673]
 tasks with computational models in a hierarchical Bayesian framework. Can perform hierarchical Bayesian analysis...

Medlda
 Referenced in 13 articles
[sw11723]
 hierarchical Bayesian topic models (e.g., LDA) under a unified constrained optimization framework, and yields latent...

HMSC
 Referenced in 2 articles
[sw22951]
 Ovaskainen et al. (2017). This framework uses Bayesian hierarchical modelling to account for environment, traits ... model species communities. In addition, this framework also include and spatially (or temporally) autocorrelated latent...

multiMarker
 Referenced in 1 article
[sw41424]
 model is framed within a Bayesian hierarchical framework, which provides flexibility to adapt to different...

POPS
 Referenced in 1 article
[sw24119]
 multilocus genotypic data. Based on a hierarchical Bayesian framework for latent regression models, POPS implements...

EcoMem
 Referenced in 1 article
[sw27702]
 data (continuous, count, proportional) applying a Bayesian hierarchical framework. The package estimates memory functions...

ADVI
 Referenced in 27 articles
[sw34040]
 inference (ADVI). The user only provides a Bayesian model and a dataset; nothing else ... probabilistic programming framework. We compare ADVI to MCMC sampling across hierarchical generalized linear models, nonconjugate...

iBAG
 Referenced in 6 articles
[sw32134]
 propose an integrative Bayesian analysis of genomics data (iBAG) framework for identifying important genes/biomarkers that ... associated with clinical outcome. This framework uses hierarchical modeling to combine the data obtained from...

MultiBUGS
 Referenced in 6 articles
[sw31621]
 implementation of the BUGS modelling framework for faster Bayesian inference. MultiBUGS implements a simple, automatic ... MCMC) algorithms for posterior inference of Bayesian hierarchical models. It builds on the existing algorithms...

BITE
 Referenced in 7 articles
[sw13222]
 event history data using flexible hierarchical models and Bayesian inference, with a particular emphasis ... distribution of lifetimes. BITE provides a framework for combining flexible baseline hazard rates and observed...

ceg
 Referenced in 1 article
[sw32871]
 models using a Bayesian framework. It provides us with a Hierarchical Agglomerative algorithm to search...

Mamba
 Referenced in 2 articles
[sw31234]
 Bayesian analysis in julia. The package provides a framework for (1) specification of hierarchical models ... options are available for MCMC sampling of Bayesian models. Individuals who are primarily interested...

PoolTestR
 Referenced in 1 article
[sw36313]
 Bayesian frameworks. Mixedeffect models allow users to account for the hierarchical sampling designs that...

Bambi
 Referenced in 2 articles
[sw36562]
 probabilistic programming framework and the ArviZ package for exploratory analysis of Bayesian models. Bambi makes ... easy to specify complex generalized linear hierarchical models using a formula notation similar to those...

fastSTRUCTURE
 Referenced in 5 articles
[sw25207]
 STRUCTURE program using a variational Bayesian framework. Variational methods pose the problem of computing relevant ... data set and a new hierarchical prior to detect weak population structure in the data...

GPflux
 Referenced in 1 article
[sw38081]
 Bayesian models, and create hierarchical models that consist of Bayesian and standard neural network layers ... single coherent framework. GPflux relies on GPflow for most of its GP objects and operations...

bacistool
 Referenced in 1 article
[sw40865]
 trials with binary outcomes using the hierarchical Bayesian classification and information sharing (BaCIS) model. Subgroups ... their outcomes mimicking the hypothesis testing framework. Subsequently, information sharing takes place within subgroups...

statFEM
 Referenced in 5 articles
[sw42054]
 data and finite element models. The Bayesian statistical framework is adopted to treat ... covariance structure. Our proposed statistical model is hierarchical in the sense that each...