scholarly journals Joint Tracking of Multiple Quantiles Through Conditional Quantiles

Author(s):  
Hugo Lewi Hammer ◽  
Anis Yazidi ◽  
Håvard Rue
2021 ◽  
pp. 1-47
Author(s):  
Qianqian Zhu ◽  
Guodong Li

Many financial time series have varying structures at different quantile levels, and also exhibit the phenomenon of conditional heteroskedasticity at the same time. However, there is presently no time series model that accommodates both of these features. This paper fills the gap by proposing a novel conditional heteroskedastic model called “quantile double autoregression”. The strict stationarity of the new model is derived, and self-weighted conditional quantile estimation is suggested. Two promising properties of the original double autoregressive model are shown to be preserved. Based on the quantile autocorrelation function and self-weighting concept, three portmanteau tests are constructed to check the adequacy of the fitted conditional quantiles. The finite sample performance of the proposed inferential tools is examined by simulation studies, and the need for use of the new model is further demonstrated by analyzing the S&P500 Index.


2021 ◽  
Vol 11 (9) ◽  
pp. 3753
Author(s):  
Hao-Lun Peng ◽  
Yoshihiro Watanabe

Dynamic projection mapping for a moving object according to its position and shape is fundamental for augmented reality to resemble changes on a target surface. For instance, augmenting the human arm surface via dynamic projection mapping can enhance applications in fashion, user interfaces, prototyping, education, medical assistance, and other fields. For such applications, however, conventional methods neglect skin deformation and have a high latency between motion and projection, causing noticeable misalignment between the target arm surface and projected images. These problems degrade the user experience and limit the development of more applications. We propose a system for high-speed dynamic projection mapping onto a rapidly moving human arm with realistic skin deformation. With the developed system, the user does not perceive any misalignment between the arm surface and projected images. First, we combine a state-of-the-art parametric deformable surface model with efficient regression-based accuracy compensation to represent skin deformation. Through compensation, we modify the texture coordinates to achieve fast and accurate image generation for projection mapping based on joint tracking. Second, we develop a high-speed system that provides a latency between motion and projection below 10 ms, which is generally imperceptible by human vision. Compared with conventional methods, the proposed system provides more realistic experiences and increases the applicability of dynamic projection mapping.


2015 ◽  
Vol 29 (6) ◽  
pp. 1203-1217 ◽  
Author(s):  
Don J. Rude ◽  
Stephen Adams ◽  
Peter A. Beling

2018 ◽  
Vol 28 (2) ◽  
pp. 217-240 ◽  
Author(s):  
Fahimah A. Al-Awadhi ◽  
Zoulikha Kaid ◽  
Ali Laksaci ◽  
Idir Ouassou ◽  
Mustapha Rachdi

Author(s):  
Yunfei Guo ◽  
Huajie Chen ◽  
Dongliang Peng ◽  
Yuesong Lin ◽  
Anke Xue

Author(s):  
Aryana Tavanai ◽  
Muralikrishna Sridhar ◽  
Eris Chinellato ◽  
Anthony G. Cohn ◽  
David C. Hogg

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