Modelling Body Mass Index Distribution using Maximum Entropy Density
The objective of this paper is to model the distribution of Body Mass Index (BMI) for a given set of covariates. BMI is one of the leading indicators of health and has been studied by health professionals for many years. As such, there have been various approaches to model the distribution of BMI....
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Published: |
2015
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| Online Access: | http://hdl.handle.net/20.500.11937/78300 |
| Summary: | The objective of this paper is to model the distribution of Body Mass Index (BMI) for a given set
of covariates. BMI is one of the leading indicators of health and has been studied by health professionals for
many years. As such, there have been various approaches to model the distribution of BMI. Furthermore, there
are numerous studies which investigate the association between an individual’s physical and socio-economic
attributes (covariates) to their BMI levels. This paper proposes the use of Maximum Entropy Density (MED)
to model the distribution of BMI using information from covariates. The paper shows how covariates can be
incorporated into the MED framework. This framework is then applied to an Australian data set. The results
show how different covariates affect different moments of the estimated BMI distribution. |
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