fit_unregularized_feature_variances: Find the variance without using the regularization
In const-ae/proDD: Identifying Differentially Abundant Proteins from Label-Free Mass Spectrometry Data
View source: R/fit_feature_parameters.R
Description
This method is important for finding the variance prior hyperparameters.
The results are similar to the unregularized results, but I cannot reuse
those because the prior estimation needs to be unbiased from former rounds
Usage
1
2
fit_unregularized_feature_variances(X, rho, zeta, experimental_design,
upper = 1000)
Details
The methods returns NA for each feature with less than 2 observations.
const-ae/proDD documentation built on Jan. 14, 2020, 9:34 a.m.
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View source: R/fit_feature_parameters.R
Description
This method is important for finding the variance prior hyperparameters. The results are similar to the unregularized results, but I cannot reuse those because the prior estimation needs to be unbiased from former rounds
Usage
1 2 | fit_unregularized_feature_variances(X, rho, zeta, experimental_design,
upper = 1000)
|
Details
The methods returns NA for each feature with less than 2 observations.
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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