• DPpackage

  • Referenced in 68 articles [sw10495]
  • probability model. In the Bayesian context, this is accomplished by placing a prior distribution ... space, such as the space of all probability distributions or the space of all regression ... precision parameter of the Dirichlet process prior, and a general purpose Metropolis sampling algorithm...
  • blasso

  • Referenced in 13 articles [sw06769]
  • from a Bayesian perspective by assigning prior probabilities to all possible models. Corresponding computational approaches...
  • MLESAC

  • Referenced in 8 articles [sw28050]
  • that little is known about the prior probabilities of the validities of the correspondences. This ... enhanced by deriving estimates of these prior probabilities. Using the priors in guided-MLESAC...
  • DREAM

  • Referenced in 7 articles [sw24746]
  • parameters. Bayes theorem states that the posterior probability, p ( H | Y ¿ ) of a hypothesis ... proportional to the product of the prior probability, p(H) of this hypothesis ... Bayesian model averaging, distributed computation, and informative/noninformative prior distributions. The DREAM toolbox supports parallel computing...
  • SSS

  • Referenced in 33 articles [sw07794]
  • high posterior probability over models. We describe algorithmic and modeling aspects, priors over the model...
  • SWIFFT

  • Referenced in 47 articles [sw11588]
  • exploited.par Our functions are set apart from prior proposals (having comparable efficiency) by a supporting ... chosen function from the family (with noticeable probability) is at least as hard as finding...
  • PairClone

  • Referenced in 2 articles [sw30712]
  • Bayesian non‐parametric models, we estimate posterior probabilities of the number, genotypes and population frequencies ... categorical Indian buffet process as a prior probability model for subclones. Column vectors of categorical...
  • qvality

  • Referenced in 1 article [sw35274]
  • false discovery rate), which corresponds to the probability that a given observation is drawn from ... standard bootstrap procedure to estimate the prior probability of a score being from the null...
  • knncat

  • Referenced in 1 article [sw11056]
  • code also handles continuous variables and prior probabilities, and does intelligent variable selection and estimation...
  • Tree-k-RHC

  • Referenced in 2 articles [sw20976]
  • model for k-RHC where the prior haplotype probability of a founder and the haplotype...
  • gvs_BUGS

  • Referenced in 4 articles [sw26317]
  • parameters as well as the prior term and model probabilities are described in detail. Guidance...
  • shallot

  • Referenced in 9 articles [sw26314]
  • compatible with the similarities are given more probability. The use of pairwise similarities ... this type of information to define a prior partition distribution for flexible Bayesian modeling ... distribution is that it allocates probability among partitions within a given number of subsets...
  • bgaPEST

  • Referenced in 2 articles [sw27873]
  • bgaPEST is related to Bayesian probability theory in which prior information about parameters is formally...
  • BUQO

  • Referenced in 4 articles [sw34653]
  • data and prior knowledge to reject this null hypothesis with high probability. Computing such tests...
  • BAS

  • Referenced in 6 articles [sw24118]
  • linear models or mixtures of g-priors in GLMs of Li and Clyde (2015) . Other ... Empirical Bayes estimates of g. Sampling probabilities may be updated based on the sampled models ... structure as an efficient hash table. Uniform priors over all models or beta-binomial prior...
  • vbmp

  • Referenced in 2 articles [sw35354]
  • Regression with Gaussian Process Priors. It estimates class membership posterior probability employing variational and sparse...
  • BMS

  • Referenced in 5 articles [sw24117]
  • hyper-g priors), 5 kinds of model priors, moreover model sampling by enumeration or various ... allow for inferring posterior inclusion and model probabilities, various moments, coefficient and predictive densities. Plotting...
  • categorical

  • Referenced in 10 articles [sw13141]
  • discusses fundamentals, such as odds ratio and probability estimation. The authors give detailed advice ... method and a learning tool requiring no prior experience with R, the text offers...
  • MCDB

  • Referenced in 1 article [sw12046]
  • limitations of prior systems. For example, MCDB can easily handle arbitrary joint probability distributions over...
  • UMATplasticity

  • Referenced in 3 articles [sw35140]
  • framework presented is used to estimate failure probabilities across temperatures in ferritic steels. The framework ... Weibull-type model without any prior assumptions. The calibration against experimental data shows important differences ... plasticity and conventional J2 plasticity. Moreover, local probability maps show that potential damage initiation sites...