> z.nnet < nnet(z ~ x + y,data = ds,size = 2, decay = .007)
# weights: 9
initial value 164.278441
iter 10 value 99.745092
.
iter 100 value 97.279519
final value 97.279519
stopped after 100 iterations
> summary(z.nnet)
a 221 network with 9 weights
options were  decay=0.007
b>h1 i1>h1 i2>h1
2.16 0.36 3.81
b>h2 i1>h2 i2>h2
5.89 4.91 2.00
b>o h1>o h2>o
3.46 5.85 8.83
Given this information, I (naively?) assumed that the forecasting
equation would be given by:
Z(i) = 3.46  5.85 * h1  8.83 * h2
where:
h1 = 2.16 + .36 * x + 3.81 * y
h2 = 5.89 + 4.91 * x  2 * y
However, when I use these formulas for prediction, I get very different
(and obviously very wrong) predictions than those given by
predict.nnet.
What am I doing wrong? Thank you in advance for any help with this
problem!
==

Thomas J. Downing
Research Assistant
Quantitative Research
Value Line, Inc.
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