Symbol Value Sum Distribution

Given a time window of size $F$, and an observation history $H$, calculates and displays the distribution of the sum of the emitted symbols values, in $F$, given $H$. That is, it evaluates $P\Big[\sum_{t=1}^{t=F} O_t \vert H \Big]$ for every possible sum $O_1 + O_2 + \cdots + O_F$. Evidently, this method assumes the symbols can be added one to another.

Note: To clarify things, let's look at an example. Suppose you are working with a model which has only two symbols, whose values are $0$ and $1$. In a time interval of $F=2$ time units, the possible symbol outcomes are $\{(0,0), (0,1), (1,0), (1,1)\}$. Thus, there are three possibilities for the sum of the symbols emitted: $\{0,1,2\}$. The symb_sum_dist() method will calculate the probability of each of these three outcomes.

Usages: symb_sum_dist( $<$object_src$>$, $<$F$>$ )

where $<$object_src$>$ is the MTK object that containing the observation history; and $<$F$>$ is the size, in time units, of the time interval considered.

Output: Prints all possible symbol sum values with their respective probability, and their average value calculated from this distribution.