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Activity Number:
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469
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Type:
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Contributed
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Date/Time:
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Wednesday, August 5, 2009 : 10:30 AM to 12:20 PM
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Sponsor:
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Social Statistics Section
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| Abstract - #305363 |
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Title:
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Nonparametric Estimation of Individual Activity Spaces
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Author(s):
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William F. Darnieder*+ and Catherine Calder and Mei-Po Kwan and Timothy L. Hawthorne and Aubrey Jackson
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Companies:
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The Ohio State University and The Ohio State University and The Ohio State University and The Ohio State University and The Ohio State University
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Address:
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1958 Neil Avenue, Columbus, OH, 43210-1247,
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Keywords:
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spatial statistics ; kernel density estimation ; activity pattern data ; geography ; L.A.FANS
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Abstract:
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Geographers have used the term activity space to describe the totality of an individual's spatial and temporal day-to-day interaction with his environment. The study of individual activity spaces has had important consequences in urban planning and in the development of transportation networks. In this work, we provide a formal mathematical definition of activity space and explore statistical approaches to estimate an individual's activity space based on observed activity pattern data. In particular, we develop kernel density estimation techniques which make use of asymmetric kernel functions to capture unobserved activity locations which are more likely to occur along the path between observed activity locations. We illustrate our methodology by applying it to activity pattern data collected as part of the Los Angeles Family and Neighborhood Survey (L.A.FANS).
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