Cover Image

Smoothing Variances Across Time: Adaptive Stochastic Volatility

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Cho, Jason B., Matteson, David S.
Format:	Preprint
Published:	2024
Subjects:	Methodology Applications Computation
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Dynamic Bayesian Item Response Model with Decomposition (D-BIRD): Modeling Cohort and Individual Learning Over Time
by: Lee, Hansol, et al.
Published: (2025)

Bayesian Estimation of Variance under Fine Stratification via Mean-Variance Smoothing
by: Mosaferi, Sepideh, et al.
Published: (2026)

Group-Sparse Smoothing for Longitudinal Models with Time-Varying Coefficients
by: Lu, Yu, et al.
Published: (2026)

Automated Gating for Flow Cytometry Data Using a Kernel-Smoothed EM Algorithm
by: de Sousa, Farhad, et al.
Published: (2025)

Towards Improved Uncertainty Quantification of Stochastic Epidemic Models Using Sequential Monte Carlo
by: Fadikar, Arindam, et al.
Published: (2024)

Space-Time Smoothing of Survey Outcomes using the R Package SUMMER
by: Li, Zehang Richard, et al.
Published: (2020)

Predictive Volatility of Machine Learning in Micro-Samples: A Regularised Assessment of Regional Poverty
by: Jamaluddin, A. H., et al.
Published: (2026)

Volatility Forecasting Using Similarity-based Parameter Correction and Aggregated Shock Information
by: Lundquist, David P., et al.
Published: (2024)

Adaptive Influence Diagnostics in High-Dimensional Regression
by: Soale, Abdul-Nasah, et al.
Published: (2025)

Adaptive tuning of Hamiltonian Monte Carlo methods
by: Akhmatskaya, Elena, et al.
Published: (2025)

Adaptive truncation of infinite sums: applications to Statistics
by: Carvalho, Luiz Max, et al.
Published: (2022)

Bayesian Matrix Factor Models for Demographic Analysis Across Age and Time
by: Zens, Gregor
Published: (2025)

Double Robust Variance Estimation with Parametric Working Models
by: Shook-Sa, Bonnie E., et al.
Published: (2024)

A Bayesian approach for fitting semi-Markov mixture models of cancer latency to individual-level data
by: Morsomme, Raphael, et al.
Published: (2024)

Bayesian Latent Class Regression and Variable Selection with Applications to Sleep Patterns Data
by: Heaney, Matthew, et al.
Published: (2025)

Bayesian Transfer Learning for High-Dimensional Linear Regression via Adaptive Shrinkage
by: Jamshidian, Parsa, et al.
Published: (2025)

Smooth hazards with multiple time scales
by: Carollo, Angela, et al.
Published: (2023)

A Bayesian Adaptive Latent Mixture Model for Zero-Inflated Weighted Brain Connectome Analysis
by: Huang, Hsin-Hsiung, et al.
Published: (2026)

Efficient Inference in First Passage Time Models
by: Liu, Sicheng, et al.
Published: (2025)

A Direct Variance Estimation (DiVE) for Meta-Analysis of Median Differences
by: Okuda, Tadahisa, et al.
Published: (2026)

Granger Causality in High-Dimensional Networks of Time Series
by: Aslan, Sipan, et al.
Published: (2024)

Prior Smoothing for Multivariate Disease Mapping Models
by: Retegui, Garazi, et al.
Published: (2026)

Gridding and Parameter Expansion for Scalable Latent Gaussian Models of Spatial Multivariate Data
by: Peruzzi, Michele, et al.
Published: (2021)

Time-variant reliability using time-dependent surrogate models
by: Marelli, Stefano, et al.
Published: (2026)

Time-Averaged Drift Approximations are Inconsistent for Inference in Drift Diffusion Models
by: Liu, Sicheng, et al.
Published: (2025)

Stochastic Gradient Variational Bayes in the Stochastic Blockmodel
by: Regueiro, Pedro, et al.
Published: (2024)

Smooth and shape-constrained quantile distributed lag models
by: Jin, Yisen, et al.
Published: (2024)

Nonlinear Causality in Time Series Networks: With Application to Motor Imagery vs Execution
by: Aslan, Sipan, et al.
Published: (2024)

Zero Variance Portfolio
by: Chang, Jinyuan, et al.
Published: (2026)

Changepoint Detection in Categorical Time Series with Application to Daily Total Cloud Cover in Canada
by: Li, Mo, et al.
Published: (2026)

Joining and splitting models with Markov melding
by: Goudie, Robert J. B., et al.
Published: (2016)

A Bayesian Approach to Modeling Variance of Intensive Longitudinal Biomarker Data as a Predictor of Health Outcomes
by: Yu, Mingyan, et al.
Published: (2024)

Granger Causality for Mixed Time Series Generalized Linear Models: A Case Study on Multimodal Brain Connectivity
by: Piancastelli, Luiza S. C., et al.
Published: (2024)

A Metadata-Only Feature-Augmented Method Factor for Ex-Post Correction and Attribution of Common Method Variance
by: Yaslioglu, Murat
Published: (2025)

R2 priors for Grouped Variance Decomposition in High-dimensional Regression
by: Aguilar, Javier Enrique, et al.
Published: (2025)

Gimbal Regression: Orientation-Adaptive Local Linear Regression under Spatial Heterogeneity
by: Otani, Yuichiro
Published: (2026)

Addressing Phase Discrepancies in Functional Data: A Bayesian Approach for Accurate Alignment and Smoothing
by: Gardella, Jacopo, et al.
Published: (2025)

Functional Analysis of Variance for Association Studies
by: Vsevolozhskaya, Olga A., et al.
Published: (2025)

Effective Degrees of Freedom for Balanced Repeated Replication and Paired Jackknife Variance Estimates: A Unified Approach via Stratum Contrasts
by: von Davier, Matthias
Published: (2026)

pintervals: an R package for model-agnostic prediction intervals
by: Randahl, David, et al.
Published: (2026)