Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

Sign In to gain access to subscriptions and/or personal tools.
Waste Management & Research
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to Saved Citations
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Request Reprints
Right arrow Add to My Marked Citations
Citing Articles
Right arrow Citing Articles via Google Scholar
Right arrow Citing Articles via Scopus
Google Scholar
Right arrow Articles by Milke, M. W.
Right arrow Articles by McBean, E. A.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Milke, M. W.
Right arrow Articles by McBean, E. A.
Social Bookmarking
Add to CiteULike   Add to Complore   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati   Add to Twitter  
What's this?

Describing variability of MSW composition data with the log-logistic distribution

Mark W. Milke

Department of Civil Engineering, University of Canterbury, Private Bag 4800, Christchurch, New Zealand, mark.milke{at}canterbury.ac.nz

Vincent Wong

Department of Civil Engineering, University of Canterbury, Private Bag 4800, Christchurch, New Zealand

Edward A. McBean

School of Engineering, University of Guelph, Guelph, Ontario, Canada

Variations in solid waste composition data are necessary as inputs to solid waste planning, yet uncertainty exists regarding which probability distributions might be generally valuable to describe the variability. Twenty-two detailed analyses of solid waste from British Columbia, Canada, were fitted to distributions using the BestFit software. Alternative distributions were ranked based on three goodness-of-fit parameters and twelve waste fractions. The log-logistic distribution was found to be the most able to fit over the wide range of composition types considered. The results were demonstrated to be insensitive to the number of waste components or to the choice of a two- or three-parameter distribution. Although other distributions were able to better match the waste composition for individual waste types, the log-logistic distribution was demonstrated to fit, overall, a wide variety of waste composition types.

Key Words: Log-logistic distribution • solid waste • composition data analysis • goodness-of-fit • BestFit: wmr 1141—1

Waste Management & Research, Vol. 26, No. 4, 355-361 (2008)
DOI: 10.1177/0734242X08089464
Add to CiteULike CiteULike   Add to Complore Complore   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati   Add to Twitter Twitter    What's this?