[R] Bayesian Neural Networks

Felipe Bhering
Sat, 10 Dec 2011 02:04:49 -0000

I wanted to do a modelling like this, many variables, will simplificate for
understanding

y1 in [a1,b1] => (weight 1) => number 1.1
y2 in [a1,b1] => (weight 1) => number 1.2
y3 in [a1,b1] => (weight 1) => number 1.3
y4 in [a1,b1] => (weight 1) => number 1.4

y5 in [a1,b1] => (weight 2) => number 2.1
y6 in [a1,b1] => (weight 2) => number 2.2
...
...
...

I have many variables and each of them i restricted to a interval. There
are many inputs and a weight to next step ( that problem won't be a single
step or maybe will be a more difficult weight). Probably i will put prioris
on some of the weights also. The weight is known, or probably will be a
priori with parameters inserted.

I wanted to estimate the vector (y1,y2,y3,y4,y5,y6) that maximize the sum
of numbers 1.1,1.2,1.3,1.4,2.1,2.2...restricted to y1*number 1.1 +
y2*number 1.2 +  y3*number 1.3 +  y4*number 1.4+  y5*number 1.5 +  y6*number
1.6 +  < H, where H is fixed.
Can I do this or is there a problem of identification here? Is there a
package in R that do this?
Thanks in advance.

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