Copertina

Time Series Forecasting with Many Predictors

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Huang, Shuo-Chieh, Tsay, Ruey S.
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Methodology
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Model Selection for Unit-root Time Series with Many Predictors
di: Huang, Shuo-Chieh, et al.
Pubblicazione: (2025)

Temporal Wasserstein Imputation: A Versatile Method for Time Series Imputation
di: Huang, Shuo-Chieh, et al.
Pubblicazione: (2024)

Supervised Dynamic PCA: Linear Dynamic Forecasting with Many Predictors
di: Gao, Zhaoxing, et al.
Pubblicazione: (2023)

Denoising and Multilinear Projected-Estimation of High-Dimensional Matrix-Variate Factor Time Series
di: Gao, Zhaoxing, et al.
Pubblicazione: (2023)

Modeling High-Dimensional Dependent Data in the Presence of Many Explanatory Variables and Weak Signals
di: Gao, Zhaoxing, et al.
Pubblicazione: (2024)

Optimal Bias-Correction and Valid Inference in High-Dimensional Ridge Regression: A Closed-Form Solution
di: Gao, Zhaoxing, et al.
Pubblicazione: (2024)

Quantile Vector Autoregression without Crossing
di: Ando, Tomohiro, et al.
Pubblicazione: (2026)

Blurring Mean Shift for Clustering Functional Data: A Scalable Algorithm and Convergence Analysis
di: Morimoto, Toshinari, et al.
Pubblicazione: (2025)

Scalable High-Dimensional Multivariate Linear Regression for Feature-Distributed Data
di: Huang, Shuo-Chieh, et al.
Pubblicazione: (2023)

Forward Regression via Gram-Schmidt Orthogonalization for Ultra-High Dimensional Linear Models
di: Chen, Jialuo, et al.
Pubblicazione: (2025)

Vector AutoRegressive Moving Average Models: A Review
di: Düker, Marie-Christine, et al.
Pubblicazione: (2024)

Disaggregating Time-Series with Many Indicators: An Overview of the DisaggregateTS Package
di: Mosley, Luke, et al.
Pubblicazione: (2023)

pencal: an R Package for the Dynamic Prediction of Survival with Many Longitudinal Predictors
di: Signorelli, Mirko
Pubblicazione: (2023)

Forecasting of Multiple Seasonal Categorical Time Series Using Fourier Series with Application to AQI Data of Kolkata
di: Ghosh, Anirban, et al.
Pubblicazione: (2026)

Autoregressive with Slack Time Series Model for Forecasting a Partially-Observed Dynamical Time Series
di: Okuno, Akifumi, et al.
Pubblicazione: (2023)

Improving Forecasts for Heterogeneous Time Series by "Averaging", with Application to Food Demand Forecast
di: Neubauer, Lukas, et al.
Pubblicazione: (2023)

ProbRes: Volatility Learning for Probabilistic Time-Series Forecasting
di: Wang, Tingting, et al.
Pubblicazione: (2026)

A Gentle Introduction to Conformal Time Series Forecasting
di: Stocker, M., et al.
Pubblicazione: (2025)

A Random-effects Approach to Regression Involving Many Categorical Predictors and Their Interactions
di: Sun, Hanmei, et al.
Pubblicazione: (2024)

Tail-Aware Density Forecasting of Locally Explosive Time Series: A Neural Network Approach
di: Dumitrescu, Elena, et al.
Pubblicazione: (2026)

SPINEX-TimeSeries: Similarity-based Predictions with Explainable Neighbors Exploration for Time Series and Forecasting Problems
di: Naser, Ahmed Z, et al.
Pubblicazione: (2024)

Sliding-Window Signatures for Time Series: Application to Electricity Demand Forecasting
di: Drobac, Nina, et al.
Pubblicazione: (2025)

Detection of a Sparse Change in High-Dimensional Time Series
di: Huang, Jingyan
Pubblicazione: (2025)

Large Scale Hierarchical Industrial Demand Time-Series Forecasting incorporating Sparsity
di: Kamarthi, Harshavardhan, et al.
Pubblicazione: (2024)

Linguistic Approach to Time Series Forecasting
di: Lande, Dmytro, et al.
Pubblicazione: (2022)

Fast Training of Mixture-of-Experts for Time Series Forecasting via Expert Loss Integration
di: Mahtout, Btissame El, et al.
Pubblicazione: (2026)

DoFlow: Flow-based Generative Models for Interventional and Counterfactual Forecasting on Time Series
di: Wu, Dongze, et al.
Pubblicazione: (2025)

Graphical Principal Component Analysis of Multivariate Functional Time Series
di: Tan, Jianbin, et al.
Pubblicazione: (2024)

A Unified Principal Components Analysis for Stationary Functional Time Series
di: Guo, Zerui, et al.
Pubblicazione: (2024)

A Frequency-Domain Approach for Integrating Multiple Functional Time Series
di: Guo, Zerui, et al.
Pubblicazione: (2026)

Forecasting Multivariate Time Series under Predictive Heterogeneity: A Validation-Driven Clustering Framework
di: Ma, Ziling, et al.
Pubblicazione: (2026)

Stationarity of Manifold Time Series
di: Zhu, Junhao, et al.
Pubblicazione: (2024)

Penalized Subgrouping of Heterogeneous Time Series
di: Crawford, Christopher M., et al.
Pubblicazione: (2024)

Network Estimation for Stationary Time Series
di: Shelley, Madeline A., et al.
Pubblicazione: (2025)

Simultaneous Estimation and Model Choice for Big Discrete Time-to-Event Data with Additive Predictors
di: Müller, Benjamin, et al.
Pubblicazione: (2025)

Wavelet Based Time Series Models with Time-Varying Thresholds
di: Davis, Rhea, et al.
Pubblicazione: (2026)

Enhancing Forecasts Using Real-Time Data Flow and Hierarchical Forecast Reconciliation, with Applications to the Energy Sector
di: Neubauer, Lukas, et al.
Pubblicazione: (2024)

An Autoregressive Model for Time Series of Random Objects
di: Bulté, Matthieu, et al.
Pubblicazione: (2024)

Hybrid Smoothing for Anomaly Detection in Time Series
di: Hofkes, Matthew, et al.
Pubblicazione: (2024)

Interpreting Time Series Forecasts with LIME and SHAP: A Case Study on the Air Passengers Dataset
di: Shukla, Manish
Pubblicazione: (2025)