- Referenced in 253 articles
- Package for Univariate and Multivariate Hierarchical Point-referenced Spatial Models. Scientists and investigators in such ... often best analyzed with Bayesian hierarchical models. Unfortunately, fitting such models involves computationally intensive Markov...
- Referenced in 221 articles
- survival data, spatio-temporal models, graphical models, and semi-parametric statistics. With so many applications ... GMRFs in complex hierarchical models, in which statistical inference is only possible using Markov Chain...
- Referenced in 134 articles
- program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation...
- Referenced in 77 articles
- that use so-called empirical hardness models to choose among their constituent solvers. This approach ... instead of runtime, and by using hierarchical hardness models that take into account different types...
- Referenced in 358 articles
- generally, any sequence allowed by the data model. The name of the language derives from ... path expression, which provides a means of hierarchic addressing of the nodes...
- Referenced in 39 articles
- SHARPE, (Symbolic Hierarchical Automated Reliability and Performance Evaluator) is a tool for specifying and analyzing ... performance, reliability and performability models. It has been installed at over 250 sites ... used as parameters of other models. This facilitates the hierarchical combination of different model types...
- Referenced in 38 articles
- Hierarchical Linear and Nonlinear Modeling (HLM). In social research and other fields, research data often ... such data requires specialized software. Hierarchical linear and nonlinear models (also called multilevel models) have ... each level. HLM not only estimates model coefficients at each level, but it also predicts ... education research due to the prevalence of hierarchical structures in data from this field...
- Referenced in 34 articles
- with random slope). 3) Nested frailty models for hierarchically clustered data (with 2 levels ... gamma random effects. 4) Joint frailty models in the context of joint modelling for recurrent...
- Referenced in 15 articles
- Tucker3 hierarchical classes analysis. This paper presents a new model for binary three ... three-mode data, called Tucker3 hierarchical classes model (Tucker3-HICLAS). This new model generalizes ... Rosenberg’s individual differences hierarchical classes model (INDCLAS) [Psychometrika ... INDCLAS model, the Tucker3-HICLAS model includes a hierarchical classification of the elements of each...
- Referenced in 75 articles
- allowing different models of computation, both untimed and timed, to be composed hierarchically ... called directors. Different directors realise different models of computation. In this paper, we formally define...
- Referenced in 12 articles
- including ruin theory), simulation of compound hierarchical models and credibility theory. The package also features...
- Referenced in 16 articles
- structural equation modeling : SmartPLS 3 includes state-of-the-art options for analyses such ... analysis (IPMA), multi-group analysis (MGA), hierarchical component models second-order models), nonlinear relationships...
- Referenced in 9 articles
- with probabilistic models, ranging from classical hierarchical models on small data sets to complex deep...
- Referenced in 8 articles
- multinomial processing tree models. Latent-class hierarchical multinomial models are an important extension ... homogeneity assumption and provide a framework for modeling parameter heterogeneity. In this article, the computer ... means of implementing latent-class hierarchical multinomial processing tree models. HMMTree computes parameter estimates, confidence...
- Referenced in 4 articles
- toolkit for implementing hierarchical Bayesian models. HBC was created because I felt like I spend ... Allow a natural implementation of hierarchal models. Enable quick and dirty debugging of models ... message passing). Allow for hierarchical models to be easily embedded in larger programs. Automatic ... goal of HBC is to compile hierarchical models into standard programming languages (like C), these...
- Referenced in 7 articles
- EBSeq: an empirical Bayes hierarchical model for inference in RNA-seq experiments. Motivation: Messenger...
- Referenced in 6 articles
- Data from Unmarked Animals. Fits hierarchical models of animal abundance and occurrence to data collected...
- Referenced in 21 articles
- hierNet: A Lasso for Hierarchical Interactions. Fits sparse interaction models for continuous and binary responses ... Tibshirani, R., (2013) ”A Lasso for Hierarchical Interactions.” Annals of Statistics...
- Referenced in 6 articles
- event history data using flexible hierarchical models and Bayesian inference, with a particular emphasis...
- Referenced in 8 articles
- HDDM: Hierarchical Bayesian estimation of the Drift-Diffusion Model in Python. The diffusion model ... been made available to quantitatively fit the model to data, current estimation methods require ... Python-based toolbox called HDDM (hierarchical drift diffusion model), which allows fast and flexible estimation ... ballistic accumulator model. HDDM requires fewer data per subject/condition than non-hierarchical methods, allows...