• RM-MEDA

  • Referenced in 35 articles [sw08554]
  • Regularity Model-Based Multiobjective Estimation of Distribution Algorithm. Under mild conditions, it can be induced ... regularity model-based multiobjective estimation of distribution algorithm (RM-MEDA) for continuous multiobjective optimization problems...
  • FastSLAM

  • Referenced in 63 articles [sw13538]
  • presents FastSLAM, an algorithm that recursively estimates the full posterior distribution over robot pose ... number of landmarks in the map. This algorithm is based on an exact factorization...
  • Eigentaste

  • Referenced in 60 articles [sw12451]
  • algorithms. In the appendix we use uniform and normal distribution models to derive analytic estimates...
  • MOPED

  • Referenced in 12 articles [sw02388]
  • optimization tool based on an estimation of distribution algorithm is proposed. The algorithm uses ... dominated sorting genetic algorithm-II and the Parzen estimator to approximate the probability density...
  • MONEDA

  • Referenced in 5 articles [sw19793]
  • with a neural network-based estimation of distribution algorithm. The extension of estimation of distribution ... multi-objective optimization evolutionary algorithms. Adapting the model-building algorithm is one way to achieve ... novel algorithm intended to overcome the drawbacks of current MOEDAs. This new algorithm ... multi-objective neural estimation of distribution algorithm (MONEDA). MONEDA uses a modified growing neural...
  • copula

  • Referenced in 143 articles [sw14499]
  • some more copula families. Methods for density, distribution, random number generation, bivariate dependence measures, perspective ... contour plots. Fitting copula models including variance estimates. Independence and serial (univariate and multivariate) independence ... nacopula’ for nested Archimedean copulas: Efficient sampling algorithms, various estimators, goodness-of-fit tests...
  • STABLE

  • Referenced in 107 articles [sw04843]
  • Numerical calculation of stable densities and distribution functions”, J. P. Nolan, Commun. Statist.-Stochastic Models ... algorithm to generate stable random variates. It also performs maximum likelihood estimation of stable parameters...
  • nacopula

  • Referenced in 47 articles [sw06778]
  • algorithms, various estimators, and goodness-of-fit tests. The package also contains related univariate distributions...
  • MATEDA

  • Referenced in 5 articles [sw07769]
  • Matlab toolbox for Estimation of Distribution Algorithms (MATEDA-2.0). The package allows the optimization ... multi-objective problems with estimation of distribution algorithms (EDAs) based on undirected graphical models...
  • AS 221

  • Referenced in 10 articles [sw27941]
  • Algorithm AS 221. Maximum likelihood estimation of a mixing distribution...
  • MultiNest

  • Referenced in 39 articles [sw10481]
  • with an associated error estimate, and produces posterior samples from distributions that may contain multiple ... robustness, as compared to the original algorithm presented in Feroz & Hobson, which itself significantly outperformed...
  • ELISA

  • Referenced in 9 articles [sw02195]
  • algorithm called ELISA (Estimated Load Information Scheduling Algorithm) for general purpose distributed computing systems. ELISA ... load scheduling. The primary objective of the algorithm is to cut down on the communication ... resulting algorithm performs almost as well as a perfect information algorithm and is superior ... other algorithms. This makes ELISA a viable and implementable load balancing algorithm...
  • copulaedas

  • Referenced in 3 articles [sw10934]
  • package copulaedas: Estimation of Distribution Algorithms Based on Copulas. This package provides a platform where ... Estimation of Distribution Algorithms (EDAs) based on copulas can be implemented and studied. It contains...
  • AS 215

  • Referenced in 10 articles [sw03873]
  • Algorithm AS 215. Maximum-likelihood estimation of the parameters of the generalized extreme-value distribution...
  • perm_mateda

  • Referenced in 1 article [sw27196]
  • mateda: A Matlab Toolbox of Estimation of Distribution Algorithms for Permutation-based Combinatorial Optimization Problems ... metaheuristic algorithms, new advances on estimation of distribution algorithms (EDAs) have shown outstanding performance when ... Matlab package, perm_mateda, of estimation of distribution algorithms on permutation problems, which has been...
  • bsa

  • Referenced in 5 articles [sw26370]
  • consider the problem of estimating an unknown distribution function in the presence of censoring under ... prior on is a mixture of Dirichlet distributions. A hyperparameter of the prior determines ... family. A Gibbs sampling algorithm to estimate the posterior distributions of the parameters of interest...
  • PROC NLMIXED

  • Referenced in 65 articles [sw11039]
  • form (normal, binomial, Poisson) or a general distribution that you code using SAS programming statements ... quasi-Newton algorithm. Successful convergence of the optimization problem results in parameter estimates along with...
  • tlmec

  • Referenced in 11 articles [sw11119]
  • distribution. An ECM algorithm is developed for computing the maximum likelihood estimates for NLMEC/LMEC with ... likelihood value as a by-product. The algorithm uses closed-form expressions ... variance of a truncated multivariate-t distribution. The proposed algorithm is implemented...
  • MEAPCA

  • Referenced in 1 article [sw34793]
  • MEAPCA: a multi-population evolutionary algorithm based on PCA for multi-objective optimization. The simulated ... regularity model based multi-objective estimated distribution algorithm, namely, RM-MEDA that adopts a segmented...
  • DPpackage

  • Referenced in 66 articles [sw10495]
  • space of all regression functions. Unfortunately, posterior distributions ranging over function spaces are highly complex ... includes models for marginal and conditional density estimation, receiver operating characteristic curve analysis, interval-censored ... prior, and a general purpose Metropolis sampling algorithm. To maximize computational efficiency, the actual sampling...