Split-plot designs and estimation methods for mixture experiments with process variables

Technometrics

Volumn 44, Issue 1, 2002, Pages 72-79

  Kowalski, Scott M ^a   Cornell, John A ^b   Vining, G Geoffrey ^c  

^a Minitab Inc   (United States)

^b UNIVERSITY OF FLORIDA   (United States)

^c VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY   (United States)

Author keywords

Mixture experiments; Process variables; REML; Split plot design

Indexed keywords

CONSTRAINT THEORY; OPTIMIZATION; PARAMETER ESTIMATION; PROCESS ENGINEERING; STATISTICAL MECHANICS;

PROCESS VARIABLES;

RANDOM PROCESSES;

EID: 0036474103     PISSN: 00401706     EISSN: None     Source Type: Journal    
DOI: 10.1198/004017002753398344     Document Type: Article

References (15)

1. A Bayesian variable-selection approach for analyzing designed experiments with complex aliasing
2. Analyzing data from mixture experiments containing process variables: A split-plot approach
3. Fractional design plans for process variables in mixture experiments
4. Mixture experiments with process variables: D-optimal orthogonal experimental designs
5. Experimental designs for four mixture components with process variables
6. Mixture designs for four components in orthogonal blocks
7. Bias in test statistics when restrictions in randomization are caused by factors
8. A new model and class of designs for mixture experiments with process variables
9. Recovery of inter-block information when block sizes are unequal