A Proportional Odds Model of Particle Pollution

A Proportional Odds Model of Particle Pollution

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 c...

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Bibliographic Details
Main Authors: Justin R. Chimka, Ege Ozdemir
Format: Article
Language:English
Published: MDPI AG 2014-08-01
Series:Environments
Subjects:
air quality index
particle pollution
linear regression
ordered logistic regression
Online Access:http://www.mdpi.com/2076-3298/1/1/54
Description
Summary: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.
ISSN:2076-3298

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