May 24, 2016
The following ‘circuit’ diagram might be helpful in following the logic flow of my algorithm.
An unbroken blue line shows the path of inheritance, dotted line demonstrates the active node’s interrogation of the preceding node, in order to determine the error locus relative to the default median inversion of blunt-precision regression. Grey line, excluded path.
Essentially, a 1-in-3 tree?
The designation of the interrogating node as x’ might be a little confusing in terms of order, (should be x ?) but I wanted to avoid clutter with the base level labels…
Constituting a ternary tree, two bits are required to encode the a-priori, inherited state.
One (control?) bit is assigned to indicate if the tree is of median or lateral inheritance.
The other (target?) bit receives its value according to the L-R lateral branch to be encoded.
In the case of the ‘median’ case inheritance, the target-bit is ‘free’ to encode on some external data set, as the discriminant of the lateral inheritance case is superfluous in this instance.
One final technical point. The computationally intensive nature of my algorithm is in contrast to the intrinsic Boolan-algebraic efficiency of the method proposed by Alex DeCastro. Perhaps my work is better considered on its merits as a PRG?
Quiz; Perhaps someone would like to explain how the cumulative probability of the two lateral legs converges to 0.625?
Suggestions welcome, as always…