fit_location_prior: Fit a Gaussian location prior over all samples
In const-ae/proDD: Identifying Differentially Abundant Proteins from Label-Free Mass Spectrometry Data
View source: R/fit_hyperparameters.R
Description
The function takes the regularized feature means. The global mu0 is the
mean of the regularized feature means. It then calculates the unregularized
feature means right of the global mean (so that missing values are less
problematic). The global variance estimate is the variance of those
unregularized values to the global mean.
Usage
1
fit_location_prior(X, mup, zeta, rho, experimental_design)
Value
list with elements mu0 and sigma20
const-ae/proDD documentation built on Jan. 14, 2020, 9:34 a.m.
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View source: R/fit_hyperparameters.R
Description
The function takes the regularized feature means. The global mu0 is the mean of the regularized feature means. It then calculates the unregularized feature means right of the global mean (so that missing values are less problematic). The global variance estimate is the variance of those unregularized values to the global mean.
Usage
1 | fit_location_prior(X, mup, zeta, rho, experimental_design)
|
Value
list with elements mu0 and sigma20
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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