up_bb_fix: EM iteration for overdispersed binomial mixture model.
In dcgerard/updogAlpha: Using Parental Data for Offspring Genotyping

EM iteration for overdispersed binomial mixture model.

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up_bb_fix(pival, p1geno, p2geno, rho, out_mu, out_rho, ocounts, osize, qarray,
  r1vec, r2vec, pk, update_pival = TRUE, update_rho = TRUE,
  update_geno = FALSE, update_outlier = TRUE, upper_rho = NULL)

`pival`	A fudge factor. The probability of not begin a mistake. Estimated if `est_fudge = TRUE`. Set to 0.99. Only used if `est_fudge = TRUE`.
`p1geno`	The current genotype of parent 1. Must be in `0:ploidy`.
`p2geno`	The current genotype of parent 1. Must be in `0:ploidy`.
`rho`	The overdispersion parameter.
`out_mu`	The outlier mean.
`out_rho`	The outlier overdispersion parameter.
`ocounts`	A vector of non-negative integers. The ith element is the number of reads of the reference allele in the ith child.
`osize`	A vector of positive integers. The ith element is the total number of reads for the ith child.
`qarray`	An three-way array of proportions. The (i, j, k)th element is the probability of an offspring having k - 1 reference alleles given that parent 1 has i - 1 refrerence alleles and parent 2 has j - 1 reference alleles. Each dimension of the array is `ploidy + 1`.
`r1vec`	A vector of prior probabilities whose ith element is the prior probability that parent 1 has i -1 copies of allele A.
`r2vec`	A vector of prior probabilities whose ith element is the prior probability that parent 2 has i -1 copies of allele A.
`pk`	The parameter space. Should all be between 0 and 1.
`update_pival`	A logical. Should we update the mixture proportion (`TRUE`) or not (`FALSE`)?
`update_rho`	A logical. Should we update the overdispersion parameters (`TRUE`) or not (`FALSE`)?
`update_geno`	A logical. Should we update the parental genotypes (`TRUE`) or not (`FALSE`)?
`update_outlier`	A logical. Should we update the outlier distribution (`TRUE`) or not (`FALSE`)?
`upper_rho`	The upperbound on the overdispersion parameter. Defaults to 1 / (ploidy + 1) which corrsponds to bounding smallest probabilities to have finite density at 0 and 1.