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Full-Text Articles in Social and Behavioral Sciences
Location-Based Modeling And Statistics Internship With Location, Inc., Yixuan Wang
Location-Based Modeling And Statistics Internship With Location, Inc., Yixuan Wang
International Development, Community and Environment (IDCE)
In the summer 2016, I had the honor to work as a GIS & statistics intern at Location, Inc. It is a Software as a Service (SaaS) private company that builds and delivers location-based big data, analytics, tools, and services. The company’s mission is to create the best location-based technologies to help businesses make well-informed decisions (Location, Inc.). I was chosen by the company’s CEO, Dr. Andrew Schiller, who is also a Clark Alumnus. During the internship period, I worked in the data science team supervised by Jonathan Glick, and my main responsibilities were handling geographical and statistical …
Death To Kappa: Birth Of Quantity Disagreement And Allocation Disagreement For Accuracy Assessment, Robert Gilmore Pontius, Marco Millones
Death To Kappa: Birth Of Quantity Disagreement And Allocation Disagreement For Accuracy Assessment, Robert Gilmore Pontius, Marco Millones
Geography
The family of Kappa indices of agreement claim to compare a map's observed classification accuracy relative to the expected accuracy of baseline maps that can have two types of randomness: (1) random distribution of the quantity of each category and (2) random spatial allocation of the categories. Use of the Kappa indices has become part of the culture in remote sensing and other fields. This article exam- ines five different Kappa indices, some of which were derived by the first author in 2000. We expose the indices' properties mathematically and illustrate their limitations graphically, with emphasis on Kappa's use of …
Statistical Methods To Partition Effects Of Quantity And Location During Comparison Of Categorical Maps At Multiple Resolutions, R. Gil Pontius
Statistical Methods To Partition Effects Of Quantity And Location During Comparison Of Categorical Maps At Multiple Resolutions, R. Gil Pontius
Geography
New generalized statistical methods to measure agreement between two maps at multiple-resolutions, where each cell in each map has a multinomial distribution among any number of categories, are presented. This methodology quantifies agreement between any two categorical maps, where either map uses fuzzy or crisp classification. The method measures the agreement at various resolutions by aggregating neighboring cells into an increasingly coarse grid. At each resolution, the method partitions the overall agreement into correct due to chance, correct due to quantity, correct due to location, error due to location, and error due to quantity. In addition, the method computes six …