The famous "birthday problem" asks for the probability for a match of birthdates (from the 366 available) in a room with 35 randomly selected people.
Using Bayesian decision theory, an algorithm for computing the probability of a match between a short count site, and each of a set of permanent counting stations showing distinct trends, was developed.
Our model assumes that neither individual search effort nor the probability of a match vary with tenure on IA; put differently, it assumes a constant exit hazard from IA to employment.
The premise behind the model is that in State 1 the probability of a match should increase with the quality of a base, but in State 2 the probability of a match should be independent of the quality score.
For the first set of initial values, we used completely even values, i.e. a 50/50 probability of a match or mismatch for each quality score.
This reduced complexity makes the probability of a match in random sequence higher than the 25% that it would be in a genome with balanced nucleotide distributions.
Parameters in State 1 show a higher rate of matches than mismatches, varying by quality score, while parameters in State 2 remain at approximately 25% probability of a match regardless of quality.
The chance similarities were assumed to be binomially distributed and therefore the mean n.p (where p, the probability of a match = 1/6 and n = total number of responses for the given traits) was assumed to have an accompanying variance npq.
As the weight of a mtDNA match between evidence- and reference-sample depends on the frequency of the found haplotype in the particular (sub population, a large mtDNA database fulfilling high quality standards is needed for the calculation of the probability of a match by chance, being an alternative explanation for the found haplotype conformity (e.g. [4]).
Statistical relevance of the found ontology matches is calculated as P-value, or a probability of a match to occur by chance, given the size of the database.
To this end, we start by calculating the probability of a match at a given locus, assuming 0, 1 or 2 allelic dropouts, respectively, have occurred at that locus.
