introduce to the count function and its applications
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Introduce to the Count Function and Its Applications. Chang-Yun Lin Institute of Statistics, NCHU. Outlines. Count function : Properties of the count function Coefficients (regular/non-regular designs) Aberration Orthogonal array Projection Isomorphism Applications Design enumeration - PowerPoint PPT PresentationTRANSCRIPT
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Introduce to the Count Function and Its
Applications
Chang-Yun Lin
Institute of Statistics, NCHU
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Outlines Count function:
Properties of the count function Coefficients (regular/non-regular designs) Aberration Orthogonal array Projection Isomorphism
Applications Design enumeration Isomorphism examination
Count Function
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𝐹 𝐴 (𝑥 )= 34𝐶𝜙−
14𝐶1+
14𝐶2−
14𝐶3+
14𝐶12−
14𝐶13−
14𝐶23−
14𝐶123
6/8 -2/8 2/8 -2/8 2/8 -2/8 -2/8 -2/8
History
Fontana, Pistone and Rogantin (2000) Indicator function (no replicates)
Ye (2003) Count function for two levels
Cheng and Ye (2004) Count function for any levels
Coefficients (
Regular fractional factorial design
Example:
10010110
4/8 0 0 0 0 0 0 4/8
Construct a regular design
Design A , generators: , defining relation:
Count function of A
Word length pattern for
Design A , generators: , defining relation:
Word length pattern
Aberration criterion For any two designs and ,
the smallest integer s.t. . has less aberration than
if has minimum aberration
If there is no design with less aberration than
𝑊𝐿𝑃=(0,0,0,3,0,0,0) 𝑊𝐿𝑃=(0,0,0 ,2 ,0 ,1 ,0) 𝑊𝐿𝑃=(0,0,0 ,1 ,2 ,0,0)
Non-regular design
Any two effects (Placket-Burman design) cannot be estimated independently of each other not fully aliased
Advantages Run size economy Flexibility
Example
Generalized word length pattern
Regular design:
;
Non-regular design
;
Orthogonal array
n runs; k factors; s levels strength d:
for any d columns, all possible combinations of symbols appear equally often in the matrix Example:
( 1, 1): 4(-1, 1): 4( 1,-1): 4(-1,-1): 4
Orthogonal array
for Example
Projection
Design A
Projection of A on factor j: Example:
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Isomorphic designs
1 2 3
I
II
III
VI
V
IV
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and are isomorphic if and only if there exist a permutation and a vector where ’s are either 0 or 1, such that
for all
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Optimal design
Is the minimum aberration design local optimal or global optimal ?
Should we find it among all designs ?
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Design enumeration
Design generation Isomorphism examination
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• Object: design enumeration for
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Projection
?A(-2)
A(-1)
A(-3)
A?
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Assembly method
OA
OA
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3/4
3/4
1/4
1/4
-1/4 -1/4
-1/4 -1/4
-1/43/4
1/43/4
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-1/43/41/43/4
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1/4 1/43/4
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-1/4 1/43/4
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Incomplete count function
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-1 10 2
-1 10 2
?
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Hierarchical structure
OA(n, k=2, 2, d)
OA(n, k=4, 2, d)
OA(n, k=3, 2, d)
… …
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𝑶𝑨(𝒏 ,𝒅+𝟏 ,𝟐 ,𝒅)
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𝑶𝑨(𝒏 ,𝟓 ,𝟐 ,𝟐)
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𝑶𝑨(𝒏 ,𝒌 ,𝟐 ,𝒅)
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MeasureAMeasure
B
MeasureB
MeasureA
Isomorphism examintion
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Object
Propose a more efficient initial screening method
Measure development for initial screening Counting vector Split-N matrix
Efficiency comparison & enhancement Technique of projection
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Counting vector
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?Theorem 4 :
Theorem 5 :
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A
Row permutation
Sign switch
Column permutation
A’
Measure
Measure (A)
Measure
Measure (A’)=
Row permutation
Sign switch
Column permutation
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Row permutation
=
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Sign switch
1
3
5
7
2
4
6
8
Positive split N vector of t=1
Negative split N vector of t=1
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Sign switch
=
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Column permutation
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Column permutation
|| t ||=1 || t ||=2 || t ||=3
Split-N matrix=
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Efficiency
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Efficiency
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Projection
D(-1)
D D’D(-2)
D(-3)
D’(-1)
D’(-2)
D’(-3)
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Simplified methods
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ComparisonsEX 6
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EX 7
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EX 8
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Summary
Count function Coefficients; aberration; orthogonal array;
projection; isomorphism Design enumeration
Assembly method: generates a design from the LOO projections
Hierarchical structure: sequentially generates designs through the assembly method
Isomorphism examination
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Thank You