untargeted_LCMS_data: Example data set containing missing values
In KechrisLab/MAI: Mechanism-Aware Imputation
untargeted_LCMS_data R Documentation
Example data set containing missing values
Description
This data set is randomly generated. We impose 30 percent missing values using
the Mixed missingness algorithm developed by Styczynski et al. Where the
parameters alpha, beta, and gamma were chosen to be 30, 70, and 40 percent,
respectively.
References
Lee JY, Styczynski MP. NS-kNN: a modified k-nearest neighbors approach for
imputing metabolomics data. Metabolomics. 2018;14(12):153.
KechrisLab/MAI documentation built on Sept. 14, 2022, 4:09 p.m.
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| untargeted_LCMS_data | R Documentation |
Example data set containing missing values
Description
This data set is randomly generated. We impose 30 percent missing values using the Mixed missingness algorithm developed by Styczynski et al. Where the parameters alpha, beta, and gamma were chosen to be 30, 70, and 40 percent, respectively.
References
Lee JY, Styczynski MP. NS-kNN: a modified k-nearest neighbors approach for imputing metabolomics data. Metabolomics. 2018;14(12):153.
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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