Using Generalized Additive Models (GAMs) for Large Datasets to Determine the Effect of Air Pollution on Human Health
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
www.ijsr.net | Open Access | Fully Refereed | Peer Reviewed International Journal

ISSN: 2319-7064

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Research Paper | Statistics | Nigeria | Volume 7 Issue 4, April 2018

Using Generalized Additive Models (GAMs) for Large Datasets to Determine the Effect of Air Pollution on Human Health

A. O. Ochugboju, A.Yawe, H. A. Odiniya, A. A. Musa

The impact of air pollution and human health has been the subject of a colossal measure of epidemiological activity. This research considers an application in the effects of air pollution and human health where generalized additive models (GAMs) are proper. However, due to the large size of data, the use of GAMs is practically inexible with existing methods. In this manner, Wood et al. (2014) developed generalized additive model tting methods for substantial data sets for the situation in which the smooth terms are replaced by using penalized cubic regression splines. We extended our analysis to ten (10) cities simultaneously using generalized additive model. Through the utilization of the environmental package from the National Morbidity, Mortality, Air Pollution study, GAMs ends up being adaptable with large data set.

Keywords: Air Pollution, Generalized Additive Models, epidemiological activity, cubic Regression Splines

Edition: Volume 7 Issue 4, April 2018

Pages: 1777 - 1782

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How to Cite this Article?

A. O. Ochugboju, A.Yawe, H. A. Odiniya, A. A. Musa, "Using Generalized Additive Models (GAMs) for Large Datasets to Determine the Effect of Air Pollution on Human Health", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=ART20181811, Volume 7 Issue 4, April 2018, 1777 - 1782

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