1-3 4-6 7-9 10-12 13-15 16-18 19-21 22-24 25-27 28-30 31-33 34-36 37-39 40-42 43-45 46-48 49-51 52-54 55-57 58-60 61-63 64-66 67-69 70-72 73-75 76-78 79-81 82-84 85-87 88-90 91-93 94-96 97-99 100-102 103-105 106-108 109-111 112-114 115-117 118-120 121-123 124-126 127-129 130-132 133-135 136-138 139-141 142-144 145-147 148-150 151-153 154-156 157-159 160-162 163
Exampleof a second-degreeequationrepresentinga rising ridge.
ˆ y
=82.71
+8.80x1
+8.19x2
-6.95x1
2
-2.07x2
-7.59x1x2
-87.69
=
- 9.02X 1
+2.97X2
were true that bias could be ignored so that the postulatedmodel function were capab xactly representing reality, then atx = (x1,x2, . . . . xk)'
E(yx) =ηx
the standardized mean squared error associated with estimatingit byˆ y x
Vx=n? σ2
would be
?
? ? ? Vˆ y
x
ereVxwill be called thevariancefunction. rmation functionof the designdefinedby
Equivalently, we may consider the
Ix
=Vx
-1
r example, for the factorial design illustrationinthe foregoing section,
4
(1
+x1
+x2 2)
Information surface for a 22factorial used as a first-order design.
The corresponding information contours.