Description Usage Arguments Details Value
Finds the prior parameter that maximizes the marginal likelihood given the prediction.
1 2 3 4 5 |
y |
A vector of observed gene counts. |
mu |
A vector of predictions from |
sf |
Vector of normalized size factors. |
calc.a
returns a prior alpha parameter assuming constant
coefficient of variation. calc.b
returns a prior beta parameter
assuming constant Fano factor. calc.k
returns a prior variance
parameter assuming constant variance.
A vector with the optimized parameter and the negative log-likelihood.
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