MIXnorm.mle: Main function for the nested EM algorithm for MIXnorm.
In S-YIN/RSEQNORM: FFPE RNA-Seq Normalization
Description
Usage
Arguments
Value
Description
Performs the nested EM algorithm to find the MLE of the mixture model.
Usage
1
MIXnorm.mle(dat, max_iter = 20, tol = 0.01)
Arguments
dat
input raw read count matrix. dim(dat)=J genes * I samples.
max_iter
maximum number of iterations for the nested EM algorithm default is 20, recommend range (10, 50).
tol
convergency criteria, default is 1e-2, recommend range (1e-5,1).
Value
A list contains the MLE of all parameters.
S-YIN/RSEQNORM documentation built on March 8, 2020, 11:16 p.m.
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Description Usage Arguments Value
Description
Performs the nested EM algorithm to find the MLE of the mixture model.
Usage
1 | MIXnorm.mle(dat, max_iter = 20, tol = 0.01)
|
Arguments
dat |
input raw read count matrix. dim(dat)=J genes * I samples. |
max_iter |
maximum number of iterations for the nested EM algorithm default is 20, recommend range (10, 50). |
tol |
convergency criteria, default is 1e-2, recommend range (1e-5,1). |
Value
A list contains the MLE of all parameters.
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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