I'm confused about what Constrain.Equal(double d, Variable<double> v) really does. The documentation says that this sets the random variable to a constant. If the random variable had been previously set to a distribution, does this put
any constraint on that distribution or does it simply redefine the random variable?
I've read 101 & the user manual cover to cover but am pretty new to this so any help is greatly appreciated.
Constrain.Equal is more commonly used for two random variables in which case it constrains the the two (previously defined) random variables to be equal.
Using it with a constant is equivalent to observing v, and there are many examples in the documentation where we observe random variables.
So, for example, if v is defined by a fixed distribution, there is nothing more to infer. Whereas if v is defined in terms of other random variables (for example it's defined in terms of a Gaussian with a random mean) then we can make inferences about those
other random variables by observing v.