ASQ

Exclusive Content & Downloads from ASQ

Random Effects Linear Models for Process Mean and Variance

Summary: We consider random effects models for both the means and variance of a process where some variations in both the mean and variance can be explained by their related covariate effects. Empirical Bayes procedures are employed to estimate covariate effects. Approaches proposed are applied to evaluate the performance of the Phase V sensors of the tactical remote sensor system of the U.S. Marine Corps in terms of their mean and variance of detection distance with respect to target types and sensitivity levels of a sensor.

Anyone with a subscription, including Site and Enterprise members, can access this article.


Other Ways to Access content:

Join ASQ

Join ASQ as a Full member. Enjoy all the ASQ member benefits including access to many online articles.

Subscribe to Journal of Quality Technology

Access this and ALL OTHER Journal of Quality Technology online articles. You'll also receive the print version by mail.

  • Topics: Quality Control
  • Keywords: Quality control (QC),Robust design,Random effects,Bayesian methods
  • Author: Sohn, So Young; Park, C.J.
  • Journal: Journal of Quality Technology