Modeling and monitoring ecological systems-a statistical process control approach

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Statistical process control monitoring of nonlinear relationships (profiles) has been the subject of much research recently. While attention is primarily given to the statistical aspects of the monitoring techniques, little effort has been devoted to developing a general modeling approach that would introduce 'uniformity of practice' in modeling nonlinear profiles (analogously with the three-sigma limits of Shewhart control charts). In this article, we use response modeling methodology (RMM) to demonstrate implementation of this approach to statistical process control monitoring of ecological relationships. Using 10 ecological models that have appeared in the literature, it is first shown that RMM models can replace (approximate) current ecological models with negligible loss in accuracy. Computer simulation is then used to demonstrate that estimated RMM models and estimated data generating ecological models achieve goodness-of-fit that is practically indistinguishable from one another. A regression-adjusted control scheme, based on control charts for the predicted median and for residuals variation, is developed and demonstrated for three types of 'out of control' scenarios.

Original languageEnglish
Pages (from-to)1233-1248
Number of pages16
JournalQuality and Reliability Engineering International
Volume30
Issue number8
DOIs
StatePublished - 1 Dec 2014

Keywords

  • Control charts
  • Ecological systems modeling and monitoring
  • Regression-adjusted control
  • Response modeling methodology

Fingerprint

Dive into the research topics of 'Modeling and monitoring ecological systems-a statistical process control approach'. Together they form a unique fingerprint.

Cite this