• DPpackage

  • Referenced in 67 articles [sw10495]
  • specification of the probability model. In the Bayesian context, this is accomplished by placing ... spaces are highly complex and hence sampling methods play a key role. This paper provides ... programs for the implementation of some Bayesian nonparametric and semiparametric models in R, DPpackage. Currently...
  • AIS-BN

  • Referenced in 25 articles [sw02223]
  • structural advantages of Bayesian networks, (2) a smooth learning method for the importance function ... used in our tests three large real Bayesian network models available to the scientific community...
  • BDgraph

  • Referenced in 12 articles [sw14815]
  • paper, we introduce a novel and efficient Bayesian framework for Gaussian graphical model determination which ... theory and computational details of the method. It is easy to implement and computationally feasible ... dimensional graphs. We show our method outperforms alternative Bayesian approaches in terms of convergence, mixing ... learning. We illustrate the efficiency of the method on a broad range of simulated data...
  • AABC

  • Referenced in 6 articles [sw16116]
  • sets is computationally infeasible. Approximate Bayesian computation (ABC) methods perform inference on model-specific parameters ... difficult. Central to the success of ABC methods is computationally inexpensive simulation of data sets ... present approximate approximate Bayesian computation” (AABC), a class of methods that extends simulation-based inference ... large number of data sets by Bayesian resampling methods. We show that under mild assumptions...
  • bmds

  • Referenced in 12 articles [sw27804]
  • FORTRAN program to implement the methods described in ”Bayesian Multidimensional Scaling and Choice of Dimension ... object configuration, along with a simple Bayesian criterion, called MDSIC, for choosing their dimension. Simulation ... presented, as are real data. Our method provides better results than does classical multidimensional scaling...
  • PyClone

  • Referenced in 9 articles [sw26928]
  • structures in cancers. PyClone is a Bayesian clustering method for grouping sets of deeply sequenced...
  • BayesLCA

  • Referenced in 8 articles [sw16118]
  • Latent Class Analysis. Bayesian Latent Class Analysis using several different methods. The BayesLCA package ... latent class analysis within a Bayesian setting. Three methods for fitting the model are provided...
  • BayesSpec

  • Referenced in 11 articles [sw38471]
  • Techniques. An implementation of methods for spectral analysis using the Bayesian framework. It includes functions ... Chain Monte Carlo). The package takes these methods predominantly from the 2012 paper ”AdaptSPEC: Adaptive...
  • stochvol

  • Referenced in 19 articles [sw19383]
  • Bayesian estimation of stochastic volatility (SV) models via Markov chain Monte Carlo (MCMC) methods...
  • BayesEstDiffusion.jl

  • Referenced in 7 articles [sw40280]
  • form expression for the likelihood. From a Bayesian computational perspective it can be casted ... with using a Markov-chain Monte-Carlo method known as data-augmentation. If unknown parameters...
  • BayesOpt

  • Referenced in 7 articles [sw12003]
  • library with state-of-the-art Bayesian optimization methods to solve nonlinear optimization, stochastic bandits...
  • dclone

  • Referenced in 13 articles [sw23656]
  • Cloning and MCMC Tools for Maximum Likelihood Methods. Low level functions for implementing maximum likelihood ... using data cloning and Bayesian Markov chain Monte Carlo methods as described in Solymos...
  • PyMC

  • Referenced in 40 articles [sw10482]
  • PyMC is a python module that implements Bayesian statistical models and fitting algorithms, including Markov ... Along with core sampling functionality, PyMC includes methods for summarizing output, plotting, goodness...
  • BAPS 2

  • Referenced in 7 articles [sw35649]
  • analysis of genetic population structure. Bayesian statistical methods based on simulation techniques have recently been ... hierarchical tree representation, from which a Bayesian model-averaged structure estimate can be extracted...
  • EWOC

  • Referenced in 4 articles [sw14553]
  • publicly available freeware that uses Bayesian methods in a dose escalation scheme to assign dose ... methodology is based on the optimal Bayesian-feasible procedure, which is designed to approach...
  • vx_dbel

  • Referenced in 3 articles [sw37455]
  • third, cutting-edge method is shown to be very efficient in the context ... exact-test p-value computations. This Bayesian-type method considers tabulated critical values as prior ... function. In this case, a nonparametric Bayesian method is proposed to compute critical values...
  • runmlwin

  • Referenced in 4 articles [sw23864]
  • data; Fast estimation via classical and Bayesian methods; Estimation of multilevel models for cross-classified...
  • epiABC

  • Referenced in 9 articles [sw23334]
  • paper we review recent Approximate Bayesian Computation (ABC) methods for the analysis of such data...
  • BUQO

  • Referenced in 4 articles [sw34653]
  • convex optimization. We propose a Bayesian uncertainty quantification method for large-scale imaging inverse problems ... method applies to all Bayesian models that are log-concave, where maximum a posteriori ... estimation is a convex optimization problem. The method is a framework to analyze the confidence ... inform decisions and conclusions. Precisely, following Bayesian decision theory, we seek to assert the structures...
  • BEAST

  • Referenced in 50 articles [sw12588]
  • cross-platform program for Bayesian phylogenetic analysis of molecular sequences. It estimates rooted, time-measured ... models. It can be used as a method of reconstructing phylogenies but is also...