13.3 Multidimensional Scaling and Seriation
165
measure of the distance between the distance matrix estimate and the given distance
matrix vectors). Iteration continues until a defined minimum of the stress function is
found; a representation of the original upper MM-dimensional space of upper NN vectors may then
be displayed from the estimated vectors.
Theory. Define the upper MM-dimensional vector space of upper NN objects by the vectors
StartLayout 1st Row 1st Column r Subscript n minus 2 2nd Column equals 3rd Column r Subscript n minus 1 Baseline q Subscript n minus 1 Baseline plus r Subscript n Baseline comma 2nd Row 1st Column Blank 3rd Row 1st Column r Subscript n minus 1 2nd Column equals 3rd Column r Subscript n Baseline q Subscript n Baseline comma EndLayoutxi =
M
Σ
μ=1
biμ ˆyμ ,
(13.11)
where ModifyingAbove y With caret Subscript mu ˆyμ are the unit vectors of the space. The Euclidean distances between these
vectors are then given by the upper N times upper NN × N distance matrix
StartLayout 1st Row 1st Column r Subscript n minus 2 2nd Column equals 3rd Column r Subscript n minus 1 Baseline q Subscript n minus 1 Baseline plus r Subscript n Baseline comma 2nd Row 1st Column Blank 3rd Row 1st Column r Subscript n minus 1 2nd Column equals 3rd Column r Subscript n Baseline q Subscript n Baseline comma EndLayoutEi j = [(xi −x j)2]1/2 .
(13.12)
If only this matrix is known and not the underlying vectors, then an estimated distance
matrix may be defined:
StartLayout 1st Row 1st Column r Subscript n minus 2 2nd Column equals 3rd Column r Subscript n minus 1 Baseline q Subscript n minus 1 Baseline plus r Subscript n Baseline comma 2nd Row 1st Column Blank 3rd Row 1st Column r Subscript n minus 1 2nd Column equals 3rd Column r Subscript n Baseline q Subscript n Baseline comma EndLayout∼Ei j = [(∼xi −∼x j)2]1/2 .
(13.13)
The estimated vectors may be formed as
StartLayout 1st Row 1st Column r Subscript n minus 2 2nd Column equals 3rd Column r Subscript n minus 1 Baseline q Subscript n minus 1 Baseline plus r Subscript n Baseline comma 2nd Row 1st Column Blank 3rd Row 1st Column r Subscript n minus 1 2nd Column equals 3rd Column r Subscript n Baseline q Subscript n Baseline comma EndLayout∼xi =
∼
M
Σ
μ=1
aiμ ˆyμ ,
(13.14)
where
StartLayout 1st Row 1st Column r Subscript n minus 2 2nd Column equals 3rd Column r Subscript n minus 1 Baseline q Subscript n minus 1 Baseline plus r Subscript n Baseline comma 2nd Row 1st Column Blank 3rd Row 1st Column r Subscript n minus 1 2nd Column equals 3rd Column r Subscript n Baseline q Subscript n Baseline comma EndLayoutaiμ = a0iμ + ziμ
(13.15)
anda Subscript 0 i mua0iμ are initial values selected at random andz Subscript i muziμ are used to propagate the vector
through iteration.
The stress functionupper SS is a normalized measure of the distance between the distance
matrix estimate and the given distance matrix vectors:
StartLayout 1st Row 1st Column r Subscript n minus 2 2nd Column equals 3rd Column r Subscript n minus 1 Baseline q Subscript n minus 1 Baseline plus r Subscript n Baseline comma 2nd Row 1st Column Blank 3rd Row 1st Column r Subscript n minus 1 2nd Column equals 3rd Column r Subscript n Baseline q Subscript n Baseline comma EndLayoutS2 =
ΣN,N
i, j=1[∼Ei j −Ei j]2
ΣN,N
i, j=1 Ei j
.
(13.16)
This may be minimized by
StartLayout 1st Row 1st Column r Subscript n minus 2 2nd Column equals 3rd Column r Subscript n minus 1 Baseline q Subscript n minus 1 Baseline plus r Subscript n Baseline comma 2nd Row 1st Column Blank 3rd Row 1st Column r Subscript n minus 1 2nd Column equals 3rd Column r Subscript n Baseline q Subscript n Baseline comma EndLayout ∂S2
∂zkμ
= 0 ,
(13.17)
but upper E Subscript i jEi j is constant and given by
StartLayout 1st Row 1st Column r Subscript n minus 2 2nd Column equals 3rd Column r Subscript n minus 1 Baseline q Subscript n minus 1 Baseline plus r Subscript n Baseline comma 2nd Row 1st Column Blank 3rd Row 1st Column r Subscript n minus 1 2nd Column equals 3rd Column r Subscript n Baseline q Subscript n Baseline comma EndLayoutB =
N,N
Σ
i, j=1
Ei j ,
(13.18)