A Collection of Methods for Left-Censored Missing Data
Imputation
![[R logo]](../../../doc/html/Rlogo.svg)
![[Up]](../../../doc/html/left.jpg)
![[Top]](../../../doc/html/up.jpg)
Documentation for package ‘imputeLCMD’ version 2.1
Help Pages
| generate.ExpressionData | Generate expression data |
| generate.RollUpMap | Generate roll up map |
| impute.MAR | imputation under MAR/MCAR hypothesis |
| impute.MAR.MNAR | Imputation under MCAR and MNAR hypothesis |
| impute.MinDet | Imputation with min value |
| impute.MinProb | Imputation by random draws |
| impute.QRILC | imputation based on quantile regression |
| impute.wrapper.KNN | Imputation with KNN |
| impute.wrapper.MLE | imputation using the EM algorithm |
| impute.wrapper.SVD | imputation based on SVD algorithm |
| impute.ZERO | Imputation by 0. |
| insertMVs | Generates missing values in data. |
| intensity_PXD000022 | Dataset PXD000022 from ProteomeXchange. |
| intensity_PXD000052 | Dataset PXD000052 from ProteomeXchange. |
| intensity_PXD000438 | Dataset PXD000438 from ProteomeXchange. |
| intensity_PXD000501 | Dataset PXD000501 from ProteomeXchange. |
| model.Selector | Identifies row in the data matrix affected by a MNAR missingness mechanism |
| pep2prot | peptide to protein roll-up |