tolerance: Tolerance for EquiNorm convergence.
In LXQin/EquiNorm: Normalize expression data using equivalently expressed genes
Description
(Optional) The function equi.gene.norm() iteratively estimates an array effect (alpha.hat[i]) for each sample. Algorithm convergence is obtained when the sum of the absolute differences of the array effects from one iteration to the next is less than the specified tolerance value. That is, iterations continue until sum(abs(alpha.hat - alpha.old)) < tolerance (or, alternatively, when the maximum number of iterations is reached see maxIter). The default value is 1E-3.
LXQin/EquiNorm documentation built on May 7, 2019, 7:59 a.m.
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Description
(Optional) The function equi.gene.norm() iteratively estimates an array effect (alpha.hat[i]) for each sample. Algorithm convergence is obtained when the sum of the absolute differences of the array effects from one iteration to the next is less than the specified tolerance value. That is, iterations continue until sum(abs(alpha.hat - alpha.old)) < tolerance (or, alternatively, when the maximum number of iterations is reached see maxIter). The default value is 1E-3.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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