Cover Image

Modeling the uncertainty on the covariance matrix for probabilistic forecast reconciliation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Carrara, Chiara, Azzimonti, Dario, Corani, Giorgio, Zambon, Lorenzo
Format:	Preprint
Published:	2025
Subjects:	Methodology Computation
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Properties of the reconciled distributions for Gaussian and count forecasts
by: Zambon, Lorenzo, et al.
Published: (2023)

Nonlinear Probabilistic Forecast Reconciliation
by: Biswas, Anubhab, et al.
Published: (2026)

Intermittent time series forecasting: local vs global models
by: Damato, Stefano, et al.
Published: (2026)

Forecasting intermittent time series with Gaussian Processes and Tweedie likelihood
by: Damato, Stefano, et al.
Published: (2025)

Discrete forecast reconciliation
by: Zhang, Bohan, et al.
Published: (2023)

Insights into regression-based cross-temporal forecast reconciliation
by: Girolimetto, Daniele, et al.
Published: (2024)

An intuitive rearranging of the Yates covariance decomposition for probabilistic verification of forecasts with the Brier score
by: Vieira, Bruno Hebling
Published: (2026)

Tail calibration of probabilistic forecasts
by: Allen, Sam, et al.
Published: (2024)

Robust regularized covariance matrix estimation: well-posedness and convergent algorithm
by: Yi, Mengxi, et al.
Published: (2026)

Robust covariance estimation and explainable outlier detection for matrix-valued data
by: Mayrhofer, Marcus, et al.
Published: (2024)

A general framework for probabilistic model uncertainty
by: Shirvaikar, Vik, et al.
Published: (2024)

Estimating the variance-covariance matrix of two-step estimates of latent variable models: A general simulation-based approach
by: Di Mari, Roberto, et al.
Published: (2025)

Inference on covariance structure in high-dimensional multi-view data
by: Mauri, Lorenzo, et al.
Published: (2025)

Change-point detection in variance-covariance matrix
by: Lin, Ying, et al.
Published: (2026)

Online robust covariance matrix estimation and outlier detection
by: Guillot, Paul, et al.
Published: (2026)

A dynamic copula model for probabilistic forecasting of non-Gaussian multivariate time series
by: Zito, John, et al.
Published: (2025)

Direct covariance matrix estimation with compositional data
by: Molstad, Aaron J., et al.
Published: (2022)

Large covariance matrix estimation with factor-assisted variable clustering
by: Li, Dong, et al.
Published: (2025)

Testing for large-dimensional covariance matrix under differential privacy
by: Sang, Shiwei, et al.
Published: (2025)

High-dimensional covariance matrix regularization using informative targets
by: Rehman, Atiq Ur, et al.
Published: (2025)

Applying non-negative matrix factorization with covariates to label matrix for classification
by: Satoh, Kenichi
Published: (2025)

Entropy regularization in probabilistic clustering
by: Franzolini, Beatrice, et al.
Published: (2023)

Hierarchical forecasting: The role of information
by: Nguyen, Minh, et al.
Published: (2026)

Multivariate reconciliation for hierarchical time series
by: Pinheiro, Ana Caroline, et al.
Published: (2026)

Handling cellwise outliers by sparse regression and robust covariance
by: Raymaekers, Jakob, et al.
Published: (2019)

Asymptotic testing of covariance separability for matrix elliptical data
by: Virta, Joni, et al.
Published: (2026)

On the uncertainty from the first-stage estimation of prognostic covariate adjustment in randomized controlled trials
by: Seya, Nodoka, et al.
Published: (2026)

Factor-guided estimation of large covariance matrix function with conditional functional sparsity
by: Li, Dong, et al.
Published: (2023)

Penalised spline estimation of covariate-specific time-dependent ROC curves
by: Rodríguez-Álvarez, María Xosé, et al.
Published: (2025)

hmmTMB: hidden Markov models with flexible covariate effects in R
by: Michelot, Théo
Published: (2022)

Scalable likelihood-based estimation and variable selection for the Cox model with incomplete covariates
by: Kwok, Ngok Sang, et al.
Published: (2024)

Highly robust factored principal component analysis for matrix-valued outlier accommodation and explainable detection via matrix minimum covariance determinant
by: Wu, Wenhui, et al.
Published: (2025)

Forecast reconciliation with non-linear constraints
by: Girolimetto, Daniele, et al.
Published: (2025)

Simplifying debiased inference via automatic differentiation and probabilistic programming
by: Luedtke, Alex
Published: (2024)

Online detection of forecast model inadequacies using forecast errors
by: Grundy, Thomas, et al.
Published: (2025)

Bridge Sampling Diagnostics
by: Micaletto, Giorgio, et al.
Published: (2025)

HIMCE: High-dimensional multiple imputation via covariance-mode updating for neuroimaging and spatiotemporal blocks
by: Huang, Hsin-Hsiung, et al.
Published: (2026)

A flexible Bayesian tool for CoDa mixed models: logistic-normal distribution with Dirichlet covariance
by: Martínez-Minaya, Joaquín, et al.
Published: (2023)

Spatially-informed transformers: Injecting geostatistical covariance biases into self-attention for spatio-temporal forecasting
by: Calleo, Yuri
Published: (2025)

Dynamic linear regression models for forecasting time series with semi long memory errors
by: Goodwin, Thomas, et al.
Published: (2024)