Change Point Detection for Airborne Particulate Matter (<i>PM</i><sub>2.5</sub>, <i>PM</i><sub>10</sub>) by Using the Bayesian Approach

Change Point Detection for Airborne Particulate Matter (<i>PM</i><sub>2.5</sub>, <i>PM</i><sub>10</sub>) by Using the Bayesian Approach

Airborne particulate matter (PM) is a key air pollutant that affects human health adversely. Exposure to high concentrations of such particles may cause premature death, heart disease, respiratory problems, or reduced lung function. Previous work on particulate matter (<inline-formula> <mat...

Full description

Bibliographic Details
Main Authors: Muhammad Rizwan Khan, Biswajit Sarkar
Format: Article
Language:English
Published: MDPI AG 2019-05-01
Series:Mathematics
Subjects:
airborne particulate matter
Bayesian approach
change point detection
likelihood ratio test
time series analysis
air quality
Online Access:https://www.mdpi.com/2227-7390/7/5/474

Internet

https://www.mdpi.com/2227-7390/7/5/474

Similar Items