• GPML

  • Referenced in 25 articles [sw12890]
  • range of functionality for Gaussian process (GP) inference and prediction. GPs are specified by mean ... ones. Several likelihood functions are supported including Gaussian and heavy-tailed for regression as well...
  • spTimer

  • Referenced in 8 articles [sw24237]
  • predicts and temporally forecasts large amounts of space-time data using [1] Bayesian Gaussian Process ... Regressive (AR) Models, and [3] Bayesian Gaussian Predictive Processes (GPP) based AR Models for spatio...
  • RobustGaSP

  • Referenced in 4 articles [sw26272]
  • Emulation. Robust parameter estimation and prediction of Gaussian stochastic process emulators. It allows for robust ... parameter estimation and prediction using Gaussian stochastic process emulator. See the reference: Mengyang Gu, Xiaojing...
  • lgcp

  • Referenced in 10 articles [sw22045]
  • spatio-temporal prediction and forecasting for log-Gaussian Cox processes. The main computational tool...
  • laGP

  • Referenced in 10 articles [sw14043]
  • laGP: Local Approximate Gaussian Process Regression. Performs approximate GP regression for large computer experiments ... based on finding small local designs for prediction (independently) at particular inputs. OpenMP and SNOW...
  • BayesNSGP

  • Referenced in 1 article [sw30769]
  • methodology, and we furthermore implement approximate Gaussian process inference to account for very large spatial ... nimble’ package, and posterior prediction for the Gaussian process at unobserved locations is provided...
  • HIBITS

  • Referenced in 1 article [sw30626]
  • binary time series using Gaussian processes with application to predicting sleep states. Motivated ... problem of predicting sleep states, we develop a mixed effects model for binary time series ... stochastic component represented by a Gaussian process. The fixed component captures the effects of covariates ... binary-valued response. The Gaussian process captures the residual variations in the binary response that...
  • MPErK

  • Referenced in 2 articles [sw23610]
  • stationary Gaussian Stochastic process models to data from a computer experiment, for predicting the output...
  • bigGP

  • Referenced in 4 articles [sw23850]
  • bigGP: Distributed Gaussian Process Calculations. Distributes Gaussian process calculations across nodes in a distributed memory ... methods for maximum likelihood with normal data, prediction, calculation of uncertainty (i.e., posterior covariance calculations...
  • GPdoemd

  • Referenced in 1 article [sw26109]
  • uses Gaussian process surrogate models to approximate and maximise the divergence between marginal predictive distributions...
  • krisp

  • Referenced in 1 article [sw14717]
  • kriging based regression (also known as Gaussian process regression) and optimization of deterministic simulators ... noisy data (correlation kernels, hyper-parameter estimation, prediction, cross validation). 2. methods implementing Expected Improvement...
  • StateSpace.jl

  • Referenced in 1 article [sw29997]
  • nonlinear, and the process noise and observation errors may be Gaussian, or from some other ... provide methods to perform the common prediction, filtering, and smoothing tasks for each type...
  • acebayes

  • Referenced in 5 articles [sw20243]
  • optimisation steps. At each step, a Gaussian process regression model is used to approximate ... goals of parameter estimation, model selection and prediction...
  • glarma

  • Referenced in 3 articles [sw23274]
  • class of observation driven non-linear non-Gaussian state space models. The state vector consists ... autoregressive-moving average (ARMA) filter of past predictive residuals. Currently three distributions (Poisson, negative binomial ... conditional on initializing values for the ARMA process) optimized using Fisher scoring or Newton Raphson...
  • emulator

  • Referenced in 2 articles [sw25521]
  • program is assumed to be a Gaussian process, whose parameters are estimated using Bayesian techniques ... number of undetermined input parameters; many climate prediction models fall into this class. The emulator...
  • GoGP

  • Referenced in 1 article [sw23912]
  • based on alternative representation of the Gaussian process under geometric and optimization views, hence termed ... GoGP delivered comparable, or slightly better, predictive performance while achieving a magnitude of computational speedup...
  • HOSA

  • Referenced in 1 article [sw21993]
  • much more information in a stochastic non-Gaussian or deterministic signal than is conveyed ... higher-order spectral analysis capabilities for signal processing applications. The toolbox is an excellent resource ... about concepts and algorithms in statistical signal processing. The HOSA Toolbox is a collection ... adaptive linear prediction are implemented. Also included are algorithms for testing of Gaussianity and Linearity...
  • ANSYS

  • Referenced in 576 articles [sw00044]
  • ANSYS offers a comprehensive software suite that spans...
  • ARfit

  • Referenced in 32 articles [sw00046]
  • ARfit is a collection of Matlab modules for...
  • ATLAS

  • Referenced in 192 articles [sw00056]
  • This paper describes the Automatically Tuned Linear Algebra...