Mineral Prospectivity Prediction from High-Dimensional Geoscientific Data Using a Similarity-Based Density Estimation Model

2011 ◽  
Vol 20 (3) ◽  
pp. 143-155 ◽  
Author(s):  
Andrew A. Skabar
Keyword(s):  
Density Estimation ◽  
High Dimensional ◽  
Estimation Model ◽  
Mineral Prospectivity ◽  
Geoscientific Data

scholarly journals Author Correction: An extended Weight Kernel Density Estimation model forecasts COVID-19 onset risk and identifies spatiotemporal variations of lockdown effects in China

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Wenzhong Shi ◽  
Chengzhuo Tong ◽  
Anshu Zhang ◽  
Bin Wang ◽  
Zhicheng Shi ◽  
...  
Keyword(s):  
Density Estimation ◽  
Kernel Density Estimation ◽  
Kernel Density ◽  
Spatiotemporal Variations ◽  
Estimation Model

A Correction to this paper has been published: https://doi.org/10.1038/s42003-021-01924-6

scholarly journals Forecasting COVID-19 onset risk and evaluating spatiotemporal variations of the lockdown effect in China

2020 ◽  
Author(s):  
Wenzhong Shi ◽  
Chengzhuo Tong ◽  
Anshu Zhang ◽  
Bin Wang ◽  
Zhicheng Shi ◽  
...  
Keyword(s):  
High Resolution ◽  
Density Estimation ◽  
Kernel Density Estimation ◽  
Symptom Onset ◽  
Kernel Density ◽  
Spatiotemporal Variations ◽  
Estimation Model ◽  
Chinese Cities ◽  
Medium Risk ◽  
The City

Abstract It is important to forecast the risk of COVID-19 symptom onset and thereby evaluate how effectively the city lockdown measure could reduce this risk. This study is a first comprehensive, high-resolution investigation of spatiotemporal heterogeneities in the effect of the Wuhan lockdown on the risk of COVID-19 symptom onset in all 347 Chinese cities. An extended Weight Kernel Density Estimation model was developed to predict the COVID-19 onset risk under two scenarios (i.e., with and without Wuhan lockdown). The Wuhan lockdown, compared with the scenario without lockdown implementation, delayed the arrival of the COVID-19 onset risk peak for 1-2 days in general and lowered risk peak values among all cities. The decrease of the onset risk attributed to the lockdown was more than 8% in over 40% of Chinese cities, and up to 21.3% in some cities. Lockdown was the most effective in areas with medium risk before lockdown.

Layer-constrained variational autoencoding kernel density estimation model for anomaly detection

2020 ◽  
Vol 196 ◽  
pp. 105753 ◽  
Author(s):  
Peng Lv ◽  
Yanwei Yu ◽  
Yangyang Fan ◽  
Xianfeng Tang ◽  
Xiangrong Tong
Keyword(s):  
Anomaly Detection ◽  
Density Estimation ◽  
Kernel Density Estimation ◽  
Kernel Density ◽  
Estimation Model

scholarly journals Spatially-Explicit Testing of a General Aboveground Carbon Density Estimation Model in a Western Amazonian Forest Using Airborne LiDAR

2015 ◽  
Vol 8 (1) ◽  
pp. 9 ◽  
Author(s):  
Patricio Molina ◽  
Gregory Asner ◽  
Mercedes Farjas Abadía ◽  
Juan Ojeda Manrique ◽  
Luis Sánchez Diez ◽  
...  
Keyword(s):  
Density Estimation ◽  
Airborne Lidar ◽  
Spatially Explicit ◽  
Carbon Density ◽  
Estimation Model ◽  
Amazonian Forest ◽  
Aboveground Carbon ◽  
Aboveground Carbon Density
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