Copertina

Computationally efficient segmentation for non-stationary time series with oscillatory patterns

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Bianco, Nicolas, Cappello, Lorenzo
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Methodology Computation
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Constructing Level Sets Using Smoothed Approximate Bayesian Computation
di: Edwards, David, et al.
Pubblicazione: (2024)

Missing data in non-stationary multivariate time series from digital studies in Psychiatry
di: Cai, Xiaoxuan, et al.
Pubblicazione: (2025)

Parametric or nonparametric: the FIC approach for stationary time series
di: Hermansen, Gudmund, et al.
Pubblicazione: (2026)

Bayesian Predictive Inference Beyond Martingales
di: Battiston, Marco, et al.
Pubblicazione: (2025)

Causal estimands and identification of time-varying effects in non-stationary time series from N-of-1 mobile device data
di: Cai, Xiaoxuan, et al.
Pubblicazione: (2024)

Bayesian variance change point detection with credible sets
di: Cappello, Lorenzo, et al.
Pubblicazione: (2022)

A new framework for non-stationary spatio-temporal data fusion of multi-fidelity models
di: Colombo, Pietro, et al.
Pubblicazione: (2026)

A portmanteau test for multivariate non-stationary functional time series with an increasing number of lags
di: Bai, Lujia, et al.
Pubblicazione: (2024)

Information matrix test for normality of innovations in stationary time series models
di: Liu, Zixuan, et al.
Pubblicazione: (2024)

Hierarchical Bayesian spectral analysis of multiple stationary time series
di: Lee, Rebecca, et al.
Pubblicazione: (2025)

Complex trend inference for high-dimensional piecewise locally stationary time series
di: Bai, Lujia, et al.
Pubblicazione: (2024)

Bayesian inference for stochastic oscillatory systems using the phase-corrected Linear Noise Approximation
di: Swallow, Ben, et al.
Pubblicazione: (2022)

Computationally efficient variational-like approximations of possibilistic inferential models
di: Cella, Leonardo, et al.
Pubblicazione: (2024)

A Bayesian framework for change-point detection with uncertainty quantification
di: Berlind, Davis, et al.
Pubblicazione: (2025)

Scalable and Robust Spatial Prediction via Multi-Resolution Ensembles of Predictive Processes
di: Bianco, Nicolas, et al.
Pubblicazione: (2026)

Nonparametric data segmentation in multivariate time series via joint characteristic functions
di: McGonigle, Euan T., et al.
Pubblicazione: (2023)

Inference for non-stationary time series quantile regression with inequality constraints
di: Sun, Yuan, et al.
Pubblicazione: (2024)

On the use of the cumulant generating function for inference on time series
di: Moor, Alban, et al.
Pubblicazione: (2024)

On the partial autocorrelation function for locally stationary time series: characterization, estimation and inference
di: Ding, Xiucai, et al.
Pubblicazione: (2024)

Discriminant Analysis in stationary time series based on robust cepstral coefficients
di: Matias, Jonathan de Souza, et al.
Pubblicazione: (2024)

HDTSA: An R package for high-dimensional time series analysis
di: Chang, Jinyuan, et al.
Pubblicazione: (2024)

Scalable Bayesian inference for time series via divide-and-conquer
di: Ou, Rihui, et al.
Pubblicazione: (2021)

Automated selection of r for stationary and nonstationary models for r largest order statistics
di: Shin, Yire, et al.
Pubblicazione: (2026)

Interpretable additive model for analyzing high-dimensional functional time series
di: Wang, Haixu, et al.
Pubblicazione: (2025)

Fast, effective, and coherent time series modeling using the sparsity-ranked lasso
di: Peterson, Ryan, et al.
Pubblicazione: (2022)

Computationally and statistically efficient estimation of time-smoothed counterfactual curves
di: Susmann, Herbert P., et al.
Pubblicazione: (2025)

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

Scalable Variational Bayes Inference for Dynamic Variable Selection
di: Bianco, Nicolas, et al.
Pubblicazione: (2023)

Coherent forecast combination for linearly constrained multiple time series
di: Girolimetto, Daniele, et al.
Pubblicazione: (2024)

Generalized method of L-moment estimation for stationary and nonstationary extreme value models
di: Shin, Yonggwan, et al.
Pubblicazione: (2025)

Forecasting high-dimensional functional time series with dual-factor structures
di: Tang, Chen, et al.
Pubblicazione: (2021)

A semi-parametric estimation method for quantile coherence with an application to bivariate financial time series clustering
di: Jiménez-Varón, Cristian F., et al.
Pubblicazione: (2023)

Inference in matrix-valued time series with common stochastic trends and multifactor error structure
di: Chen, Rong, et al.
Pubblicazione: (2025)

A new class of non-stationary Gaussian fields with general smoothness on metric graphs
di: Bolin, David, et al.
Pubblicazione: (2025)

Factorized Binary Search: change point detection in the network structure of multivariate high-dimensional time series
di: Ondrus, Martin, et al.
Pubblicazione: (2021)

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

An efficient Monte Carlo method for valid prior-free possibilistic statistical inference
di: Martin, Ryan
Pubblicazione: (2025)

Stratified distance space improves the efficiency of sequential samplers for approximate Bayesian computation
di: Pesonen, Henri, et al.
Pubblicazione: (2023)

Dynamic SIR/SEIR-like models comprising a time-dependent transmission rate: Hamiltonian Monte Carlo approach with applications to COVID-19
di: Inouzhe, Hristo, et al.
Pubblicazione: (2023)

Factor pre-training in Bayesian multivariate logistic models
di: Mauri, Lorenzo, et al.
Pubblicazione: (2024)