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Environments 2014, 1(1), 54-59; doi:10.3390/environments1010054

A Proportional Odds Model of Particle Pollution

Department of Industrial Engineering, University of Arkansas, 800 W. Dickson St., Fayetteville, AR 72701, USA
Author to whom correspondence should be addressed.
Received: 25 May 2014 / Revised: 4 August 2014 / Accepted: 4 August 2014 / Published: 12 August 2014
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A linear regression model of particle pollution and an ordered logistic regression model of the relevant index were selected for observations in the US city of Los Angeles, California. Models were used to forecast Air Quality Index (AQI) from a sample, and were compared and contrasted. Methods are comparable overall but markedly different in their powers to predict certain categories. Linear regression models of AQI through particle pollution are more favored to predict moderate air quality; ordered logistic regression models of AQI directly are more favored to predict good air quality. View Full-Text
Keywords: air quality index; particle pollution; linear regression; ordered logistic regression air quality index; particle pollution; linear regression; ordered logistic regression
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Chimka, J.R.; Ozdemir, E. A Proportional Odds Model of Particle Pollution. Environments 2014, 1, 54-59.

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