mv_maximization: Multivariate maximization
In benja0x40/Tightrope: ChIP-seq normalization according to background reads density
Description
Usage
Arguments
Value
See Also
Description
Multivariate maximization
Usage
1
mv_maximization(x, theta, p, mle_fun = mv_mle)
Arguments
x
numeric matrix representing multivariate data where rows = observations
and columns = samples or conditions.
theta
list of multivariate distribution parameters
p
vector of probabilities
mle_fun
maximum likelyhood estimator function (default = mv_mle)
Value
mv_maximization returns a list of multivariate distribution
parameters.
See Also
mv_expectation,
mv_emloop
benja0x40/Tightrope documentation built on May 24, 2019, 1:35 a.m.
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Description Usage Arguments Value See Also
Description
Multivariate maximization
Usage
1 | mv_maximization(x, theta, p, mle_fun = mv_mle)
|
Arguments
x |
numeric matrix representing multivariate data where rows = observations and columns = samples or conditions. |
theta |
list of multivariate distribution parameters |
p |
vector of probabilities |
mle_fun |
maximum likelyhood estimator function (default = mv_mle) |
Value
mv_maximization returns a list of multivariate distribution
parameters.
See Also
mv_expectation, mv_emloop
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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