Data Driven Estimation of Imputation Error-A Strategy for Imputation with a Reject Option.
Missing data is a common problem in many research fields and is a challenge that always needs careful considerations. One approach is to impute the missing values, i.e., replace missing values with estimates. When imputation is applied, it is typically applied to all records with missing values indi...
Main Authors: | Nikolaj Bak, Lars K Hansen |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2016-01-01
|
Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC5056679?pdf=render |
Similar Items
-
Data-driven Missing Data Imputation for Wind Farms Using Context Encoder
by: Wenlong Liao, et al.
Published: (2022-01-01) -
Reuse of imputed data in microarray analysis increases imputation efficiency
by: Yi Gwan-Su, et al.
Published: (2004-10-01) -
On imputing UNHCR data
by: Moritz Marbach
Published: (2018-10-01) -
ExtraImpute: a novel machine learning method for missing data imputation
by: Alabadla, Mustafa, et al.
Published: (2022) -
Assessment of Imputation Quality: Comparison of Phasing and Imputation Algorithms in Real Data
by: Katharina Stahl, et al.
Published: (2021-09-01)