This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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161
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Type:
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Topic Contributed
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Date/Time:
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Monday, August 2, 2010 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistics and the Environment
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Abstract - #307397 |
Title:
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Modeling Categorized and Aggregated Dive Depth Data from Marine Mammals
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Author(s):
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Megan Higgs*+ and Jay Ver Hoef
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Companies:
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Montana State University and NOAA
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Address:
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2-242 Wilson Hall, Bozeman, MT, 59717, USA
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Keywords:
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ordinal ;
Bayesian ;
hierarchical ;
temporal
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Abstract:
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Ordinal variables are pervasive in ecological and environmental data, often arising from practical constraints imposed at data collection. Variables hypothetically measured on a continuous scale are instead recorded as ordered categories. Ironically, this simplification complicates a statistical analysis. Models based on cumulative probabilities are developing sophistication to account for temporal, spatial, and/or cluster dependence, conceptually connecting the ordinal response to a latent continuous random variable through a vector of cut-points used to clip the continuous distribution. Dependence is induced through correlation among the continuous variables. We provide extensions for data acquired from Time-Depth Recorders affixed to Harbor seals by the NOAA National Marine Mammal Lab, where dive depth is recorded as a depth category, and data are aggregated over 6-hr intervals.
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Authors who are presenting talks have a * after their name.
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