Copula-based semiparametric models for spatiotemporal data.
Sign Up to like & getrecommendations! Published in 2019 at "Biometrics"
DOI: 10.1111/biom.13066
Abstract: The joint analysis of spatial and temporal processes poses computational challenges due to the data's high dimensionality. Furthermore, such data are commonly non-Gaussian. In this paper, we introduce a copula-based spatiotemporal model for analyzing spatiotemporal… read more here.
Keywords: copula based; method; spatiotemporal data; semiparametric models ... See more keywords
Forest-Based and Semiparametric Methods for the Postprocessing of Rainfall Ensemble Forecasting
Sign Up to like & getrecommendations! Published in 2019 at "Weather and Forecasting"
DOI: 10.1175/waf-d-18-0149.1
Abstract: To satisfy a wide range of end users, rainfall ensemble forecasts have to be skillful for both low precipitation and extreme events. We introduce local statistical postprocessing methods based on quantile regression forests and gradient… read more here.
Keywords: rainfall ensemble; based semiparametric; semiparametric methods; forecasting forest ... See more keywords
Forecasts of Value-at-Risk and Expected Shortfall in the Crude Oil Market: A Wavelet-Based Semiparametric Approach
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DOI: 10.3390/en13143700
Abstract: We propose the use of wavelet-based semiparametric models for forecasting the value-at-risk (VaR) and expected shortfall (ES) in the crude oil market. We compared the forecast outcomes across different time scales for three semiparametric models,… read more here.
Keywords: wavelet based; crude oil; risk; based semiparametric ... See more keywords