Design Characteristics | | |
Number of design points | GENERATE | N=number |
Saturated design | GENERATE | N=SATURATED |
Augmented design | GENERATE | AUGMENT=SAS-data-set |
Bayesian optimal design | MODEL | / PRIOR=p1,p2, ... |
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Optimality Criteria | | |
Minimize trace of (X'X)-1 | GENERATE | CRITERION=A |
Maximize |X'X| | GENERATE | CRITERION=D |
Minimize mean minimum | GENERATE | CRITERION=U |
distance to design | | |
Maximize mean distance | GENERATE | CRITERION=S |
between nearest design points | | |
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Model Specification | | |
Specify independent effects | MODEL | effects |
Exclude intercept term | MODEL | effects NOINT |
Specify class variables | CLASS | variables |
Static coding | PROC OPTEX | CODING=STATIC |
Orthogonal coding | PROC OPTEX | CODING=ORTH |
Orthogonal coding with | PROC OPTEX | CODING=ORTHCAN |
respect to candidates only | | |
Suppress coding of effects | PROC OPTEX | NOCODE |
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Block Specification | | |
Specify general covariance | BLOCKS | COVAR=SAS-data-set
<options> |
matrix for runs | | VAR=variables |
Specify general covariate model | BLOCKS | DESIGN=SAS-data-set
<options> |
Specify b blocks of size k | BLOCKS | STRUCTURE=(b)k
<options> |
Options for block specifications | | |
Repeat the search n times | | ITER=n |
Retain best m searches | | KEEP=m |
Select initial design at random | | INIT=RANDOM |
Select initial design in order | | INIT=CHAIN |
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Initial Design Characteristics | | |
Random and sequential methods | GENERATE | INITDESIGN=PARTIAL<(m)> |
Random initial design | GENERATE | INITDESIGN=RANDOM |
Sequential initial design | GENERATE | INITDESIGN=SEQUENTIAL |
Specify initial design | GENERATE | INITDESIGN=SAS-data-set |
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