• PITCON

  • Referenced in 259 articles [sw04244]
  • solving systems of nonlinear equations. Chapter 7: Parametrized systems of equations. Continuation methods, in particular ... equations approach, the code PITCON and simplicial approximation of manifolds are contained. (netlib contin...
  • MISER3

  • Referenced in 81 articles [sw04190]
  • idea of control parametrization in which the controls are approximated by piecewise constant or piecewise...
  • Church

  • Referenced in 50 articles [sw08946]
  • PCFGs, planning by inference, and various non-parametric clustering models. Finally, we show ... query on any Church program, exactly and approximately, using Monte Carlo techniques...
  • ParLinSys

  • Referenced in 19 articles [sw06461]
  • solution set of parametric interval linear systems and an inner approximation of the solution enclosure...
  • AABC

  • Referenced in 6 articles [sw16116]
  • Approximate Bayesian computation (ABC) methods perform inference on model-specific parameters of mechanistically motivated parametric ... inexpensive simulation of data sets from the parametric model of interest. However, when simulating data ... inference is not straightforward. We present approximate approximate Bayesian computation” (AABC), a class of methods ... mechanistic statistical model that approximates the correct parametric model and enables efficient simulation...
  • PhyML

  • Referenced in 11 articles [sw10915]
  • sound statistical framework (the non-parametric bootstrap and the approximate likelihood ratio test). (http://packages.ubuntu.com...
  • vx_dbel

  • Referenced in 3 articles [sw37455]
  • Distributions and K-Sample Comparisons. In practice, parametric likelihood-ratio techniques are powerful statistical tools ... distribution-free test statistics that efficiently approximate parametric likelihood ratios to analyze and compare distributions...
  • T-IFISS

  • Referenced in 8 articles [sw23889]
  • estimates of the error reduction for enhanced approximations. These error reduction indicators are used ... adaptive refinement of spatial and parametric components of Galerkin approximations. The results of numerical tests...
  • BLSURF

  • Referenced in 5 articles [sw10379]
  • surfaces are approximated by polynomial or rational parametric patches as is the case for most ... closely approximates the geometry of the surface. It consists of meshing a 2D parametric domain...
  • Resampling Stats

  • Referenced in 12 articles [sw06019]
  • parametric and non-parametric tests based on complicated mathematics and arcane approximations, the basic resampling...
  • ssym

  • Referenced in 5 articles [sw14396]
  • semi-parametric functions, whose non-parametric components may be approximated by natural cubic splines...
  • MsdeParEst

  • Referenced in 17 articles [sw25419]
  • Estimation in Mixed-Effects Stochastic Differential Equations. Parametric estimation in stochastic differential equations with random ... drift, or in the diffusion or both. Approximate maximum likelihood methods are used. M. Delattre...
  • BayesGESM

  • Referenced in 2 articles [sw22576]
  • presence of a non-parametric components approximated by using B-splines...
  • BSL

  • Referenced in 1 article [sw29747]
  • alternative to standard, non-parametric approximate Bayesian computation (ABC). BSL assumes a multivariate normal distribution ... estimator to the normal density. A semi-parametric version of BSL (semiBSL...
  • frailtypack

  • Referenced in 40 articles [sw06070]
  • hazard function but also a parametric estimation. 1) A shared gamma frailty model ... smoothing parameter is possible using an approximated cross-validation procedure. 2) Additive frailty models...
  • spdep

  • Referenced in 33 articles [sw04578]
  • Moran’s I and Getis/Ord G, saddlepoint approximations and exact tests for global and local ... spatial regression models, semi-parametric and Moran eigenvector spatial filtering, GM SAR error models...
  • bsa

  • Referenced in 5 articles [sw26370]
  • conditions that a parametric model is believed to hold approximately. We use a Bayesian approach ... this prior concentrates its mass around the parametric family. A Gibbs sampling algorithm to estimate...
  • SmoothHazard

  • Referenced in 4 articles [sw14710]
  • intensities or a semi-parametric approach with M-splines approximation of baseline intensities in order ... conducted by likelihood maximization in the parametric approach or penalized likelihood maximization in the semi...
  • MEANS

  • Referenced in 1 article [sw27253]
  • tool implementing an efficient moment expansion approximation with parametric closures that integrates well with ... system. In addition to the approximation method our package provides numerous tools to help...
  • sIPOPT

  • Referenced in 3 articles [sw06885]
  • from estimating sensitivities for parametric NLPs, the program provides approximate NLP solutions for nonlinear model...