:: Library Catalog

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Xehetasun bibliografikoak
Egile Nagusiak:	Wang, Xiaoqian, Kang, Yanfei, Hyndman, Rob J, Li, Feng
Formatua:	Preprint
Argitaratua:	2020
Gaiak:	Applications Computation
Sarrera elektronikoa:	https://arxiv.org/abs/2007.09577
Etiketak:	Etiketa erantsi Etiketarik gabe, Izan zaitez lehena erregistro honi etiketa jartzen!

Antzeko izenburuak

Another look at forecast trimming for combinations: robustness, accuracy and diversity
nork: Wang, Xiaoqian, et al.
Argitaratua: (2022)

Forecast Linear Augmented Projection (FLAP): A free lunch to reduce forecast error variance
nork: Yang, Yangzhuoran Fin, et al.
Argitaratua: (2024)

Anomaly detection using surprisals
nork: Hyndman, Rob J, et al.
Argitaratua: (2026)

Comparing Malaria Trends in the Comoros Islands: ARIMA Modeling and Retrospective Analysis
nork: Baidoo, D., et al.
Argitaratua: (2025)

Predicting Bad Goods Risk Scores with ARIMA Time Series: A Novel Risk Assessment Approach
nork: Gond, Bishwajit Prasad
Argitaratua: (2025)

Combining Probabilistic Forecasts of Intermittent Demand
nork: Wang, Shengjie, et al.
Argitaratua: (2023)

Crop Yield Time-Series Data Prediction Based on Multiple Hybrid Machine Learning Models
nork: Yan, Yueru, et al.
Argitaratua: (2025)

Predicting NVIDIA's Next-Day Stock Price: A Comparative Analysis of LSTM, MLP, ARIMA, and ARIMA-GARCH Models
nork: Xing, Yiluan, et al.
Argitaratua: (2024)

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

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

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

Modeling and forecasting of European Carbon Emission Allowance futures by ARIMA-TX-GARCH models with correlation threshold
nork: Lee, Jaeho, et al.
Argitaratua: (2025)

Functional Time Series Forecasting of Distributions: A Koopman-Wasserstein Approach
nork: Wang, Ziyue, et al.
Argitaratua: (2025)

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

Comprehensive Forecasting of California's Energy Consumption: A Multi-Source and Sectoral Analysis Using ARIMA and ARIMAX Models
nork: Moslemi, Zahra, et al.
Argitaratua: (2024)

Context-Alignment: Activating and Enhancing LLM Capabilities in Time Series
nork: Hu, Yuxiao, et al.
Argitaratua: (2025)

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

Fourier Series-Based Approximation of Time-Varying Parameters in Ordinary Differential Equations
nork: Fitzpatrick, Anna, et al.
Argitaratua: (2021)

Bayesian Statistical Inversion for High-Dimensional Computer Model Output and Spatially Distributed Counts
nork: Barnett, Steven D., et al.
Argitaratua: (2025)

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

On a Semiparametric Stochastic Volatility Model
nork: Feng, Yudong, et al.
Argitaratua: (2025)

The Effects of Air Pollution on Health: A Longitudinal Study of Los Angeles County Accounting for Measurement Error
nork: Qu, Yanfei, et al.
Argitaratua: (2024)

Modelling Loss of Complexity in Intermittent Time Series and its Application
nork: Li, Jie, et al.
Argitaratua: (2024)

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

Recovery-Informed Forecasting Strategy Enhancement
nork: Li, Feng, et al.
Argitaratua: (2026)

Fourier‐Series‐Based Application Modeling for Monthly Hydropower Generation
nork: Zong‐chang Yang
Argitaratua: (2025)

Deep Autocorrelation Modeling for Time-Series Forecasting: Progress and Prospects
nork: Wang, Hao, et al.
Argitaratua: (2026)

Multivariate Time Series Data Imputation via Distributionally Robust Regularization
nork: Liao, Che-Yi, et al.
Argitaratua: (2026)

Online conformal inference for multi-step time series forecasting
nork: Wang, Xiaoqian, et al.
Argitaratua: (2024)

The Promise of Time-Series Foundation Models for Agricultural Forecasting: Evidence from Commodity Prices
nork: Wang, Le, et al.
Argitaratua: (2026)

Explainable Educational AI: Integrating Symbolic Reasoning and Diffusion Models for Transparent Knowledge Tracing
nork: Feng Feng, et al.
Argitaratua: (2026)

Time Series Transformer-Based Modeling of Pavement Skid and Texture Deterioration
nork: Gao, Lu, et al.
Argitaratua: (2025)

Distribution-Free Prediction Bands for Multivariate Functional Time Series: an Application to the Italian Gas Market
nork: Diquigiovanni, Jacopo, et al.
Argitaratua: (2021)

Spatial-temporal evolution characteristics and driving factors of carbon emission prediction in China-research on ARIMA-BP neural network algorithm
nork: Sanglin, Zhao, et al.
Argitaratua: (2024)

Rumor Forwarding Prediction Model Based on Uncertain Time Series
nork: Wang, Ruihong, et al.
Argitaratua: (2024)

Innovation ARIMA models application to predict pressure variations in water supply networks with open-loop control. Case study in Noja (Cantabria, Spain)
nork: Munoz-Rodriguez, David, et al.
Argitaratua: (2025)

Structured Learning in Time-dependent Cox Models
nork: Wang, Guanbo, et al.
Argitaratua: (2023)

Network Modeling of Asynchronous Change-Points in Multivariate Time Series
nork: McKee, Carson, et al.
Argitaratua: (2025)

State-Space Modeling of Shape-constrained Functional Time Series
nork: Hiraki, Daichi, et al.
Argitaratua: (2024)

Time Series based Ensemble Model Output Statistics for Temperature Forecasts Postprocessing
nork: Jobst, David, et al.
Argitaratua: (2024)