up_fix: Fixed-point iteration for updog EM.
In dcgerard/updogAlpha: Using Parental Data for Offspring Genotyping

Fixed-point iteration for updog EM.

1 2	up_fix(pival, p1geno, p2geno, alpha, beta, ocounts, osize, ldbinommat, qarray, r1vec, r2vec, update_pi = TRUE, update_geno = TRUE, update_beta = TRUE)

`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 genotype of parent 1
`p2geno`	The genotype of parent 2
`alpha`	The alpha parameter in the beta distribution of the outliers. Only used if `est_fudge = TRUE`.
`beta`	The beta parameter in the beta distribution of the outliers. Only used if `est_fudge = TRUE`.
`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.
`ldbinommat`	The log binomial densities of the counts. The rows index the parental genotypes and the columns index the individuals.
`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.
`update_pi`	A logical. Should we update the fudge factor (`TRUE`) or not (`FALSE`)?
`update_geno`	A logical. Should we update the parental genotypes (`TRUE`) or not (`FALSE`)?
`update_beta`	A logical. Should we update the outlier model `TRUE` or not (`FALSE`)?