What is he best known for?
The fields of study he is best known for:
- Statistics
- Law
- Artificial intelligence
The scientist’s investigation covers issues in Statistics, Econometrics, Cartography, Index of dissimilarity and Modifiable areal unit problem.
His work deals with themes such as Multivariate interpolation and Interpolation, which intersect with Statistics.
His studies in Interpolation integrate themes in fields like Algorithm and Variogram, Kriging.
His Cartography study combines topics from a wide range of disciplines, such as Census tract and Unit.
His studies deal with areas such as Univariate, Multivariate statistics and Scale as well as Modifiable areal unit problem.
His research in Scale intersects with topics in Bivariate analysis, Multivariate analysis, Logistic regression and Ethnic group.
His most cited work include:
- The Modifiable Areal Unit Problem in Multivariate Statistical Analysis (845 citations)
- An adaptive inverse-distance weighting spatial interpolation technique (611 citations)
- Geographic information system (255 citations)
What are the main themes of his work throughout his whole career to date?
David W. S. Wong mostly deals with Statistics, Geographic information system, Spatial analysis, Econometrics and Data mining.
His research in the fields of Modifiable areal unit problem, Spatial correlation, Index of dissimilarity and Sample size determination overlaps with other disciplines such as Set.
His study in Geographic information system is interdisciplinary in nature, drawing from both Visualization, Geospatial analysis and Data science.
His Data science study combines topics in areas such as Enterprise GIS and GIS and public health.
David W. S. Wong works in the field of Spatial analysis, focusing on Spatial descriptive statistics in particular.
His research on Econometrics frequently connects to adjacent areas such as Set.
He most often published in these fields:
- Statistics (20.31%)
- Geographic information system (20.31%)
- Spatial analysis (16.41%)
What were the highlights of his more recent work (between 2016-2021)?
- Economic geography (7.81%)
- Statistics (20.31%)
- Spatial analysis (16.41%)
In recent papers he was focusing on the following fields of study:
David W. S. Wong mainly investigates Economic geography, Statistics, Spatial analysis, Data mining and Redistricting.
As part of the same scientific family, David W. S. Wong usually focuses on Economic geography, concentrating on China and intersecting with Polarization.
David W. S. Wong brings together Statistics and Data reliability to produce work in his papers.
His Spatial analysis research incorporates themes from Population density, Moving average and Variables.
His studies deal with areas such as Standard error and Choropleth Mapping as well as Data mining.
His Redistricting study deals with House of Representatives intersecting with State and Demography.
Between 2016 and 2021, his most popular works were:
- Comparing implementations of global and local indicators of spatial association (163 citations)
- Big Data Science: Opportunities and Challenges to Address Minority Health and Health Disparities in the 21st Century (46 citations)
- Taking the pulse of COVID-19: a spatiotemporal perspective (35 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Law
- Artificial intelligence
David W. S. Wong focuses on Statistical inference, Software, Data mining, 2019-20 coronavirus outbreak and Pulse.
His Statistical inference research incorporates a variety of disciplines, including Spatial ecology and Space.
His biological study spans a wide range of topics, including GeoDa, Spatial analysis and CrimeStat.
His Data mining research incorporates elements of Machine learning, Data set, Range, Data quality and Process.
A majority of his 2019-20 coronavirus outbreak research is a blend of other scientific areas, such as China, Severe acute respiratory syndrome coronavirus 2, Perspective and Economic geography.
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