• CAViaR

  • Referenced in 158 articles [sw04424]
  • current information, the conditional autoregressive value at risk (CAViaR) model specifies the evolution...
  • DEoptim

  • Referenced in 42 articles [sw08656]
  • Markov-Switching Generalized AutoRegressive Conditional Heteroskedasticity (MSGARCH) model for the returns of the Swiss Market...
  • fGarch

  • Referenced in 25 articles [sw09994]
  • package fGarch: Rmetrics - Autoregressive Conditional Heteroskedastic Modelling: Environment for teaching ”Financial Engineering and Computational Finance...
  • acp

  • Referenced in 4 articles [sw23280]
  • exhibiting autoregressive properties, using the Autoregressive Conditional Poisson model (ACP(p,q)) proposed by Heinen...
  • PReMiuM

  • Referenced in 10 articles [sw14746]
  • effects in the response model, where a spatial CAR (conditional autoregressive) term can be also...
  • CARramps

  • Referenced in 1 article [sw24455]
  • Reparameterized and Marginalized Posterior Sampling for Conditional Autoregressive Models. This package fits Bayesian conditional autoregressive...
  • Spatial Statistics

  • Referenced in 8 articles [sw06026]
  • autoregressions (SAR), conditional spatial autoregressions (CAR), and mixed regressive spatially autoregressive (MRSA) models. In addition...
  • CARrampsOcl

  • Referenced in 1 article [sw22935]
  • Independent sampling for Bayesian normal conditional autoregressive models with OpenCL acceleration A new computational strategy ... class of Bayesian spatial and spatiotemporal conditional autoregressive models. The method is based on reparameterization...
  • ACDm

  • Referenced in 1 article [sw31468]
  • package ACDm: Tools for Autoregressive Conditional Duration Models. Package for Autoregressive Conditional Duration (ACD, Engle...
  • CARBayes

  • Referenced in 9 articles [sw15288]
  • modelled by a set of random effects, which are assigned a conditional autoregressive (CAR) prior ... random effects, including a multivariate CAR (MCAR) model for multivariate spatial data. Full details...
  • DySco

  • Referenced in 5 articles [sw16261]
  • Dynamic Conditional Score (DCS) or Generalized Autoregressive Score (GAS) time series models have attracted considerable...
  • ARCHModels.jl

  • Referenced in 1 article [sw36552]
  • ARCH models in Julia. ARCH (Autoregressive Conditional Heteroskedasticity) models are a class of models designed...
  • ARCH

  • Referenced in 2 articles [sw27756]
  • ARCH models in Python: Autoregressive Conditional Heteroskedasticity (ARCH) and other tools for financial econometrics, written...
  • spBFA

  • Referenced in 1 article [sw31476]
  • process. Areal spatial data is modeled using a conditional autoregressive (CAR) prior and point-referenced ... Gaussian process. The response variable can be modeled as Gaussian, probit, Tobit, or Binomial (using...
  • spGARCH

  • Referenced in 1 article [sw26932]
  • spatial and spatiotemporal autoregressive conditional heteroscedasticity (spatial ARCH and GARCH models) by Otto, Schmid, Garthoff ... parameters of spARCH models and spatial autoregressive models with spARCH disturbances, diagnostic checks, visualizations...
  • CARBayesST

  • Referenced in 2 articles [sw15512]
  • temporal autocorrelation is modelled by random effects, which are assigned conditional autoregressive (CAR) style prior...
  • MaskGAN

  • Referenced in 3 articles [sw31828]
  • models are often autoregressive language models or seq2seq models. These models generate text by sampling ... words sequentially, with each word conditioned on the previous word, and are state...
  • MADE

  • Referenced in 9 articles [sw36209]
  • powerful generative models. Our method masks the autoencoder’s parameters to respect autoregressive constraints: each ... interpreted as a set of conditional probabilities, and their product, the full joint probability...
  • glarma

  • Referenced in 5 articles [sw23274]
  • driven non-linear non-Gaussian state space models. The state vector consists of a linear ... observation driven component consisting of an autoregressive-moving average (ARMA) filter of past predictive residuals ... available. Estimation is via maximum likelihood (conditional on initializing values for the ARMA process) optimized ... testing for serial dependence in generalized linear model settings. Graphical diagnostics including model fits, autocorrelation...
  • BayesPiecewiseICAR

  • Referenced in 0 articles [sw16051]
  • using a Hierarchical Bayesian model with an Intrinsic Conditional Autoregressive formulation for the spatial dependency...