mv_mle: Multivariate normal distribution: maximum likelihood...
In benja0x40/Tightrope: ChIP-seq normalization according to background reads density
Description
Usage
Arguments
Value
See Also
Description
Multivariate normal distribution: maximum likelihood estimation
Usage
1
Arguments
x
numeric matrix representing multivariate data where rows = observations
and columns = samples or conditions.
w
numeric weight (i.e. probability) associated to observations
ML
logical (reserved, default = TRUE)
Value
mv_mle returns a list with the following elements:
mu
mean vector
sigma
covariance matrix
See Also
mv_pdf,
mv_rsg,
mv_gmm
benja0x40/Tightrope documentation built on May 24, 2019, 1:35 a.m.
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Description Usage Arguments Value See Also
Description
Multivariate normal distribution: maximum likelihood estimation
Usage
1 |
Arguments
x |
numeric matrix representing multivariate data where rows = observations and columns = samples or conditions. |
w |
numeric weight (i.e. probability) associated to observations |
ML |
logical (reserved, default = TRUE) |
Value
mv_mle returns a list with the following elements:
mu |
mean vector |
sigma |
covariance matrix |
See Also
mv_pdf, mv_rsg, mv_gmm
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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