Scale‐dependent blending of ensemble rainfall nowcasts and numerical weather prediction in the open‐source pysteps library
Flash flood early warning requires accurate rainfall forecasts with a high spatial and
temporal resolution. As the first few hours ahead are already not sufficiently well captured by …
temporal resolution. As the first few hours ahead are already not sufficiently well captured by …
Stacking and ridge regression-based spectral ensemble preprocessing method and its application in near-infrared spectral analysis
H Huang, Z Fang, Y Xu, G Lu, C Feng, M Zeng, J Tian… - Talanta, 2024 - Elsevier
Spectral preprocessing techniques can, to a certain extent, eliminate irrelevant information,
such as current noise and stray light from spectral data, thereby enhancing the performance …
such as current noise and stray light from spectral data, thereby enhancing the performance …
Rethinking satellite data merging: from averaging to SNR optimization
Merging of multiple satellite datasets is a simple yet effective way to reduce prediction error.
However, most merging methods for satellite data today are based on weighted averaging …
However, most merging methods for satellite data today are based on weighted averaging …
Improving box office projections through sentiment analysis: Insights from regularization-based forecast combinations
The increasing reliance on box office revenue as a real activity tracker necessitates a
deeper understanding of how sentiment affects this micro-level indicator. Although previous …
deeper understanding of how sentiment affects this micro-level indicator. Although previous …
Forecast combination puzzle in the HAR model
The heterogeneous autoregressive (HAR) model has become the benchmark model for
predicting realized volatility, given its simplicity and consistent empirical performance. Many …
predicting realized volatility, given its simplicity and consistent empirical performance. Many …
[HTML][HTML] On the uncertainty of a combined forecast: The critical role of correlation
The purpose of this paper is to show that the effect of the zero-correlation assumption in
combining forecasts can be huge, and that ignoring (positive) correlation can lead to …
combining forecasts can be huge, and that ignoring (positive) correlation can lead to …
[HTML][HTML] Flexible global forecast combinations
Forecast combination–the aggregation of individual forecasts from multiple experts or
models–is a proven approach to economic forecasting. To date, research on economic …
models–is a proven approach to economic forecasting. To date, research on economic …
High Moment Constraints for Predictive Density Combination
LL Pauwels, P Radchenko, AL Vasnev - 2020 - papers.ssrn.com
Financial data typically exhibit asymmetry and heavy tails, which makes forecasting the
entire density of the returns critically important. We investigate the effects of aggregating, or …
entire density of the returns critically important. We investigate the effects of aggregating, or …
[HTML][HTML] Так ли плохи отрицательные веса в объединении прогнозов?
АА Сурков - Статистика и экономика, 2023 - cyberleninka.ru
Цель исследования. В настоящей работе предлагается рассмотреть проблему
отрицательности весовых коэффициентов при объединении прогнозов. Объединение …
отрицательности весовых коэффициентов при объединении прогнозов. Объединение …
A scientometrics review on combining forecasts in financial markets
Combining forecasts has been widely applied as one of the approaches to increase the
predictive power over the past few decades. With the promising results, it has seen an …
predictive power over the past few decades. With the promising results, it has seen an …