forecasting

Yang Xiao

Ph.D. Student, Statistics
Yang Xaio research specializes in the development of advanced spatio-temporal models and Bayesian frameworks.

Time Series Clustering: Pattern Recognition, Forecasting, and Amortized Inference

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B9 R2325

This talk presents innovative time series clustering techniques, highlighting a quantile-based approach for analyzing locally stationary data, a predictive framework for enhanced forecasting, and the use of amortized inference to overcome traditional algorithmic limitations.

Statistical Analysis of Multi-day Solar Irradiance using a Threshold Time Series model

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B9 H2 R2325

Abstract The analysis of solar irradiance has important applications in predicting solar energy production from solar power plants. Although the sun provides every day more energy than we need, the variability caused by environmental conditions affects electricity production. Most of the existing statistical models to forecast solar irradiance are linear and highly depend on normality assumptions. However, solar irradiance shows strong non-linearity and is only measured during the day time. Thus, we propose a new multi-day threshold autoregressive (TAR) model to quantify the variability of the