Photo from wikipedia
ABSTRACT Replicating runs in designed experiments is good practice. The most important reason to replicate runs is to allow for a model-independent estimate of the error variance. Without the pure… Click to show full abstract
ABSTRACT Replicating runs in designed experiments is good practice. The most important reason to replicate runs is to allow for a model-independent estimate of the error variance. Without the pure error degrees of freedom provided by replicated runs, the error variance will be biased if the fitted model is missing an active effect. This work provides a replication strategy for full-factorial designs having two to four factors. However, our approach is general and could be applied to any factorial experiment.
Keywords:
two level;
factorial designs;
replication small;
small two;
partial replication;
replication
Journal Title: Quality Engineering
Year Published: 2017
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!
Journal Title: Quality Engineering
Year Published: 2017
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!