We’ve released the newest version of NIMBLE on CRAN and on our website. NIMBLE is a system for building and sharing analysis methods for statistical models, especially for hierarchical models and computationally-intensive methods (such as MCMC, Laplace approximation, and SMC). Version 1.3.0 provides some new and improved functionality, plus some ...

We’ve released the newest version of NIMBLE on CRAN and on our website. NIMBLE is a system for building and sharing analysis methods for statistical models, especially for hierarchical models and computationally-intensive methods (such as MCMC, Laplace approximation, and SMC). This release provides provides extensive new functionality, including: A ...

We’ve released the newest version of NIMBLE on CRAN and on our website. NIMBLE is a system for building and sharing analysis methods for statistical models, especially for hierarchical models and computationally-intensive methods (such as MCMC,Laplace approximation, and SMC). This release provides new functionality as well as various ...

nimbleHMC provides Hamiltonian Monte Carlo samplers for use with NIMBLE, in particular NUTS samplers. NIMBLE’s HMC samplers can be flexibly assigned to a subset of model parameters, allowing users to consider various sampling configurations. We’ve released version 0.2.0 of nimbleHMC, which includes a new default NUTS sampler inspired by ...

We’ve released the newest version of NIMBLE on CRAN and on our website. NIMBLE is a system for building and sharing analysis methods for statistical models, especially for hierarchical models and computationally-intensive methods (such as MCMC and SMC). Version 1.0.1 follows shortly after 1.0.0 and fixes an issue and a bug ...

We’ve released the newest version of NIMBLE on CRAN and on our website. NIMBLE is a system for building and sharing analysis methods for statistical models, especially for hierarchical models and computationally-intensive methods (such as MCMC and SMC). Version 1.0.0 provides substantial new functionality. This includes: A Laplace approximation algorithm ...

We’ve released the newest version of NIMBLE on CRAN and on our website. NIMBLE is a system for building and sharing analysis methods for statistical models, especially for hierarchical models and computationally-intensive methods (such as MCMC and SMC). Version 0.13.0 provides new functionality (in particular improved handling of predictive nodes ...

We’ll be holding a virtual training workshop on NIMBLE, January 4-6, 2023 from 8 am to 1 pm US Pacific (California) time each day. NIMBLE is a system for building and sharing analysis methods for statistical models, especially for hierarchical models and computationally-intensive methods (such as MCMC and SMC). Recently we added ...

We’re excited to announce that NIMBLE now supports automatic differentiation (AD), also known as algorithmic differentiation, in a beta version available on our website. In this beta version, NIMBLE now provides: Hamiltonian Monte Carlo (HMC) sampling for an entire parameter vector or arbitrary subsets of the parameter vector (i....

We’ve released the newest version of NIMBLE on CRAN and on our website. NIMBLE is a system for building and sharing analysis methods for statistical models, especially for hierarchical models and computationally-intensive methods (such as MCMC and SMC). Version 0.12.2 is a bug fix release. In particular, this release fixes ...

We’ll be holding a in-person training workshop on NIMBLE, June 1-3, 2022, in Lisbon, Portugal, sponsored by the Centro de Estatística e Aplicações at the Universidade Lisboa (CEAUL). NIMBLE is a system for building and sharing analysis methods for statistical models, especially for hierarchical models and computationally-intensive methods (...

We’ll be giving a two-hour tutorial on NIMBLE, sponsored by the environmental Bayes (enviBayes) section of ISBA (The International Society for Bayesian Analysis), on Thursday November 18, from 11 am to 1 pm US Eastern time. NIMBLE (r-nimble.org) is a system for fitting and programming with hierarchical models in R that ...

We’ve released the newest version of NIMBLE on CRAN and on our website. NIMBLE is a system for building and sharing analysis methods for statistical models, especially for hierarchical models and computationally-intensive methods (such as MCMC and SMC). Version 0.12.1, in combination with version 0.12.0 (which was released just last week), ...

(Prepared by Chris Paciorek and Sally Paganin.) Once one has samples from an MCMC, one often wants to do some post hoc manipulation of the samples. An important example is posterior predictive sampling, which is needed for posterior predictive checking. With posterior predictive sampling, we need to simulate new data ...

We’ve released the newest version of NIMBLE on CRAN and on our website. NIMBLE is a system for building and sharing analysis methods for statistical models, especially for hierarchical models and computationally-intensive methods (such as MCMC and SMC). Version 0.11.1 is a bug fix release, fixing a bug that was ...

We’ve released the newest version of NIMBLE on CRAN and on our website. NIMBLE is a system for building and sharing analysis methods for statistical models, especially for hierarchical models and computationally-intensive methods (such as MCMC and SMC). Version 0.11.0 provides a variety of new functionality, improved error trapping, and ...

We’ll be holding a virtual training workshop on NIMBLE, May 26-28, from 8 am to 1 pm US Pacific (California) time each day. NIMBLE is a system for building and sharing analysis methods for statistical models, especially for hierarchical models and computationally-intensive methods (such as MCMC and SMC). The workshop will ...

We’ve released the newest version of NIMBLE on CRAN and on our website. NIMBLE is a system for building and sharing analysis methods for statistical models, especially for hierarchical models and computationally-intensive methods (such as MCMC and SMC). We’ve released version 0.10.1.  Version 0.10.1 is primarily a bug fix release: –  ...

We’ve moved NIMBLE’s various sequential Monte Carlo (SMC) algorithms (bootstrap particle filter, auxiliary particle filter, ensemble Kalman filter, iterated filter2, and particle MCMC algorithms) to the new nimbleSMC package. So if you want to use any of these methods as of nimble version 0.10.0, please make sure to install ...