• VEGAS

• Referenced in 52 articles [sw07171]
• algorithm of Lepage is based on importance sampling. It samples points from the probability distribution...

• AIS-BN

• Referenced in 25 articles [sw02223]
• adaptive importance sampling algorithm for evidential reasoning in large Bayesian networks Stochastic sampling algorithms, while ... this problem, we propose an adaptive importance sampling algorithm, AIS-BN, that shows promising convergence ... based on the theoretical properties of importance sampling in finite-dimensional integrals and the structural ... sampling algorithms, likelihood weighting and self-importance sampling. We used in our tests three large...

• EVPI

• Referenced in 20 articles [sw02644]
• EVPI-based importance sampling solution procedures for multistage stochastic linear programmes on parallel MIMD architectures ... parallel version of a sequential importance sampling solution algorithm based on local expected value...

• CosmoMC

• Referenced in 18 articles [sw16206]
• analysing Monte-Carlo samples and importance sampling (plus a suite of scripts for building grids...

• Hmisc

• Referenced in 41 articles [sw04530]
• utility operations, functions for computing sample size and power, importing datasets, imputing missing values, advanced...

• AdMit

• Referenced in 8 articles [sw09498]
• target distribution and to efficiently generate a sample of random draws from it, given only ... density of interest. Then, importance sampling or the independence chain Metropolis-Hastings algorithm is used ... density, using the fitted mixture as the importance or candidate density. The estimation procedure ... compared to standard cases of importance sampling and the Metropolis-Hastings algorithm using a naive...

• loo

• Referenced in 10 articles [sw19420]
• cross-validation (LOO) using Pareto smoothed importance sampling (PSIS), a new procedure for regularizing importance...

• SiZer

• Referenced in 65 articles [sw34664]
• important question is which observed features are “really there,” as opposed to being spurious sampling...

• LAS

• Referenced in 18 articles [sw17180]
• data. The search for sample-variable associations is an important problem in the exploratory analysis...

• MitISEM

• Referenced in 4 articles [sw23111]
• Mixture of Student t Distributions using Importance Sampling and Expectation Maximization. Flexible multivariate function approximation ... distribution is obtained using Importance Sampling weighted Expectation Maximization algorithm...

• bsa

• Referenced in 5 articles [sw26370]
• mass around the parametric family. A Gibbs sampling algorithm to estimate the posterior distributions ... parameters of interest is reviewed. An importance sampling scheme enables us to use the output...

• networksis

• Referenced in 5 articles [sw08215]
• graphs with fixed marginals through sequential importance sampling. Tools to simulate bipartite networks/graphs with...

• CTBN-RLE

• Referenced in 5 articles [sw12961]
• implements exact inference and Gibbs and importance sampling approximate inference for any type of evidence...

• PLASMA

• Referenced in 5 articles [sw18420]
• efficient simulation engine and uses importance sampling to reduce the number and length of simulations...

• FastGCN

• Referenced in 3 articles [sw38089]
• Learning with Graph Convolutional Networks via Importance Sampling. The graph convolutional networks (GCN) recently proposed ... this work---FastGCN. Enhanced with importance sampling, FastGCN not only is efficient for training...

• EpiStruct

• Referenced in 2 articles [sw34639]
• code to support the paper: Importance sampling for partially observed temporal epidemic models. We present ... importance sampling algorithm that can produce realisations of Markovian epidemic models that exactly match observations ... over a period of time. The importance sampling can be used to construct an efficient ... particle marginal Metropolis Hastings scheme, the importance sampling provides a large speed-up in terms...

• DECIS

• Referenced in 4 articles [sw21978]
• Carlo pre-sampling. When using Monte Carlo sampling the user has the option of employing ... using as variance reduction techniques importance sampling or control variates, based on either an additive...

• Shift

• Referenced in 4 articles [sw18322]
• such as the Consistent Adjoint-Driven Importance Sampling methodology, advanced parallel decompositions, and tally methods...

• exactLoglinTest

• Referenced in 3 articles [sw25926]
• sequentially rounded normal approximation and importance sampling to approximate probabilities from the conditional distribution. Usually...

• cosmoabc

• Referenced in 3 articles [sw20219]
• algorithm, which uses an adaptive importance sampling scheme. The code is very flexible...