• MersenneTwister

  • Referenced in 351 articles [sw05367]
  • twister: A 623-dimensionally equidistributed uniform pseudo-random number generator. A new algorithm called Mersenne ... pseudorandom numbers. For a particular choice of parameters, the algorithm provides a super astronomical period...
  • Algorithm 829

  • Referenced in 60 articles [sw04467]
  • function. Then, all other necessary parameters are generated randomly for all 100 functions...
  • SQG

  • Referenced in 19 articles [sw00907]
  • having in mind continuous distributions of random parameters and nonlinear optimization problems. They are suited...
  • STABLE

  • Referenced in 110 articles [sw04843]
  • generate stable random variates. It also performs maximum likelihood estimation of stable parameters and some...
  • PROC NLMIXED

  • Referenced in 70 articles [sw11039]
  • approximation to the likelihood integrated over the random effects. Different integral approximations are available ... convergence of the optimization problem results in parameter estimates along with their approximate standard errors ... random effects. You can also estimate arbitrary functions of the nonrandom parameters, and PROC NLMIXED...
  • BacSim

  • Referenced in 22 articles [sw17261]
  • eight readily obtainable parameters which can be randomly varied. For substrate diffusion, a two-dimensional ... simulator output faithfully reproduced all input parameters. Growth characteristics when maintenance and uptake rates were ... loss of synchrony due to random variation of cell parameters or spatial heterogeneity. Variation...
  • RanGen

  • Referenced in 56 articles [sw14333]
  • construct random networks which satisfy preset values of the parameters used to control the hardness...
  • abcrf

  • Referenced in 19 articles [sw21308]
  • package abcrf: ABC random forests for Bayesian parameter inference. Approximate Bayesian computation (ABC) has grown ... conduct likelihood-free Bayesian inferences about parameters with no prior selection of the relevant components ... tolerance level. The approach relies on the random forest methodology of Breiman (2001) applied ... random forest for each component of the parameter vector of interest. When compared with earlier...
  • bnlearn

  • Referenced in 77 articles [sw08265]
  • learning and inference. Bayesian network structure learning, parameter learning and inference. This package implements constraint ... Some utility functions (model comparison and manipulation, random data generation, arc orientation testing, simple ... included, as well as support for parameter estimation (maximum likelihood and Bayesian) and inference, conditional...
  • mlrnd

  • Referenced in 41 articles [sw20908]
  • matrix of IID random numbers distributed according to the one-parameter Mittag-Leffler distribution with...
  • Rchoice

  • Referenced in 5 articles [sw23114]
  • Binary, Poisson and Ordered) Models with Random Parameters. An implementation of simulated maximum likelihood method ... Logit) and Poisson models with random parameters for cross-sectional and longitudinal data...
  • MRG32k3a

  • Referenced in 29 articles [sw18715]
  • Good parameters and implementations for combined multiple recursive random number generators. Combining parallel multiple recursive ... sequences provides an efficient way of implementing random number generators with long periods and good ... made extensive computer searches for good parameter sets, with respect to the spectral test...
  • gbs

  • Referenced in 25 articles [sw06078]
  • reliability indicators and random number generators from GBS distributions. Parameter estimates for censored and uncensored...
  • MCCEFF

  • Referenced in 5 articles [sw06179]
  • based FEM, where Taylor expansion with random parameters is not necessary now and is simply ... material properties defined as Gaussian random variables, other composite parameters as well as other probabilistic...
  • SPOT

  • Referenced in 87 articles [sw06347]
  • common approaches in simulation and optimization. Sequential parameter optimization has been developed, because there ... tree-based models such as CART and random forest; Gaussian process models (Kriging), and combinations...
  • LSD

  • Referenced in 9 articles [sw14340]
  • such as density and distribution functions, random numbers, parameters estimate, and goodness of data fitting...
  • gmnl

  • Referenced in 5 articles [sw23110]
  • package gmnl: Multinomial Logit Models with Random Parameters. An implementation of maximum simulated likelihood method ... estimation of multinomial logit models with random coefficients. Specifically, it allows estimating models with continuous...
  • HGLMMM

  • Referenced in 6 articles [sw08092]
  • Gaussian or gamma distribution. The distribution of random effects can be specified as Gaussian, gamma ... designs can be handled. Further, dispersion parameters of random components and the residual dispersion (overdispersion ... modeled as a function of covariates. Overdispersion parameter can be fixed or estimated. Fixed effects...
  • GUI-HDMR

  • Referenced in 22 articles [sw07924]
  • input parameters can be controlled, then a quasi-random sampling method is preferable. This guarantees...
  • wbs

  • Referenced in 94 articles [sw11110]
  • sample size. Due to a certain random localisation mechanism, WBS works even for very short ... choice of a window or span parameter, and does not lead to a significant increase...