• MPT

  • Referenced in 235 articles [sw04732]
  • field of computational geometry and multi-parametric optimization. The toolbox offers a broad spectrum ... systems with persistent additive and polytopic uncertainties. Users can add custom constraints, such as polytopic...
  • bootlib

  • Referenced in 461 articles [sw40642]
  • errors, confidence intervals, and other measures of uncertainty for a wide range of problems. This ... methods for use with single samples from parametric and nonparametric models. Chapter 3 extends...
  • LFR-toolbox

  • Referenced in 29 articles [sw04756]
  • uncertain models, regular and singular parametric expressions, more general uncertainty blocks (nonlinear, time-varying...
  • Skew

  • Referenced in 8 articles [sw14905]
  • uncertain closed loop, subject to LTI parametric uncertainties, neglected dynamics and to some extent uncertain...
  • SReach

  • Referenced in 5 articles [sw20158]
  • nonlinear) hybrid automata with parametric uncertainty. The second one is probabilistic hybrid automata with additional...
  • CLM

  • Referenced in 2 articles [sw39321]
  • metrics is challenged by forcing uncertainty, parametric uncertainty, and model structural complexity, but the multivariate...
  • FAMOUS

  • Referenced in 2 articles [sw36917]
  • assessment of robustness of systems to parametric uncertainties. Hence, FAMOUS provides the solution of both...
  • UncertainSCI

  • Referenced in 1 article [sw41879]
  • modern techniques to estimate model and parametric uncertainty, with a particular emphasis on needs...
  • PAROC

  • Referenced in 6 articles [sw21878]
  • suite of multi-parametric programming techniques for optimisation under uncertainty, explicit/multi-parametric MPC and state-estimation...
  • AUTO-IK

  • Referenced in 2 articles [sw21228]
  • program for the automated non-parametric modeling of local uncertainty in earth sciences. Indicator kriging...
  • bootComb

  • Referenced in 1 article [sw41191]
  • bootComb: Combine Parameter Estimates via Parametric Bootstrap. Propagate uncertainty from several estimates when combining these ... function. This is done by using the parametric bootstrap to simulate values from the distribution...
  • HyStar

  • Referenced in 0 articles [sw24785]
  • affected by both time varying parametric uncertainties and persistent exterior disturbances. The robust tracking...
  • QPsimplex

  • Referenced in 5 articles [sw31751]
  • parametric value-at-risk minimization, portfolio optimization, and robust optimization with ellipsoidal objective uncertainty...
  • Bchron

  • Referenced in 2 articles [sw11012]
  • relative sea level rate estimation, and non-parametric phase modelling. This package enables quick calibration ... estimation incorporating time uncertainty in polynomial regression models; and non-parametric phase modelling via Gaussian...
  • PROPOSAL

  • Referenced in 1 article [sw16807]
  • systematic error rather than statistical uncertainties. Such an error source is the Monte Carlo description ... implemented for different parametrizations. Thus, a full study of the systematic uncertainties is possible from...
  • ActSNClass

  • Referenced in 1 article [sw39934]
  • parametric feature extraction method, Random Forest classifier and two learning strategies (uncertainty sampling and random...
  • torcpy

  • Referenced in 1 article [sw33488]
  • different data, parametric searches and algorithms used in numerical optimization and Bayesian uncertainty quantification...
  • ADDT

  • Referenced in 1 article [sw17543]
  • parametric and semiparametric approaches allow one to do statistical inference such as quantifying uncertainties...
  • GGMnonreg

  • Referenced in 1 article [sw40478]
  • methods consist of multiple regression, a non-parametric bootstrap , and Fisher ... transformed partial correlations . Parameter uncertainty, predictability, and network replicability
  • mBART

  • Referenced in 2 articles [sw41499]
  • avoiding the further confines of a full parametric form. For such monotone relationships, mBART provides ... predictive performance, and (iii) less post-data uncertainty. While many key aspects of the unconstrained...