get_cov_mle: Calculate the negative inverse hessian of the parameters from...
In dcgerard/updogAlpha: Using Parental Data for Offspring Genotyping

This is the covariance matrix if evaluated at the MLE's of these parameters.

get_cov_mle(ocounts, osize, ploidy, prob_geno, bias_val, seq_error, od_param,
  out_prop, p1counts = NULL, p1size = NULL, p1geno = NULL,
  p2counts = NULL, p2size = NULL, p2geno = NULL, bias_val_mean = 0,
  bias_val_sd = 0.7, seq_error_mean = -4.7, seq_error_sd = 1,
  model = c("f1", "s1", "hw", "uniform"))

`ocounts`	The observed counts of the refernce allele for each individual.
`osize`	The observed number of reads for each individuals.
`ploidy`	An integer. The ploidy of the species. This is assumed to be the same for each individual.
`prob_geno`	The allele frequencies of the genotypes. See `get_prob_geno`.
`bias_val`	The bias parameter. A value of 1 means there is no bias toward one allele or the other. A value less than one indicates a bias toward the reference allele. A value greater than one indicates a bias toward the non-reference allele.
`seq_error`	The sequencing error rate.
`od_param`	The overdispersion parameter in the beta-binomial model for the OK counts. When this is zero, this resorts to the binomial model for counts.
`out_prop`	The proportion of points that are outliers. Defaults (quite arbitrarily) to `0.01`.
`p1counts`	A vector of non-negative integers. The ith element is the number of reads of the reference allele in the ith sample of parent 1. If `NULL` then the prior probabilities on parent 1's genotype will default to uniform.
`p1size`	A vector of positive integers. The ith element is the total number of reads in the ith sample of parent 1. If `NULL` then the prior probabilities on parent 1's genotype will default to uniform.
`p1geno`	The initial value of the first parental genotype.
`p2counts`	A vector of non-negative integers. The ith element is the number of reads of the reference allele in the ith sample of parent 2. If `NULL` then the prior probabilities on parent 2's genotype will default to uniform.
`p2size`	A vector of positive integers. The ith element is the total number of reads in the ith sample of parent 2. If `NULL` then the prior probabilities on parent 2's genotype will default to uniform.
`p2geno`	The initial value of the second parental genotype.
`bias_val_mean`	The prior mean on the log of `bias_val` (corresponding to `parvec[1]`). Set `bias_val_sd = Inf` to have no penalty on the bias parameter.
`bias_val_sd`	The prior standard deviation on the log of `bias_val` (corresponding to `parvec[1]`). Set `bias_val_sd = Inf` to have no penalty on the bias parameter.
`seq_error_mean`	The mean of the logit-normal prior on the sequencing error rate, which corresponds to `parvec[2]`. Set `seq_error_sd = Inf` to have no penalty on the sequencing error rate. The default is -4.7, which roughly corresponds to a mean sequencing error value of 0.009. If you want to constain `seq_error` to be zero, you need to set `update_seq_error = FALSE`, `seq_error = 0`, and`seq_error_mean = -Inf`.
`seq_error_sd`	The standard deviation of the logit-normal prior on the sequencing error rate, which corresponds to `parvec[2]`. The default is 1, which at three standard deviations is about a sequencing error rate of 0.15. Set `seq_error_sd = Inf` to have no penalty on the sequencing error rate.
`model`	The model for the genotype distribution. Do we assume an F1 population (`"f1"`), an S1 population (`"s1"`), Hardy-Weinberg equilibrium (`"hw"`), or a uniform distribution (`"uniform"`).