Imputing missing values using cumulative linear regression

Imputing missing values using cumulative linear regression

The concept of missing data is important to apply statistical methods on the dataset. Statisticians and researchers may end up to an inaccurate illation about the data if the missing data are not handled properly. Of late, Python and R provide diverse packages for handling missing data. In this stud...

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Bibliographic Details
Main Author: Samih M. Mostafa
Format: Article
Language:English
Published: Wiley 2019-07-01
Series:CAAI Transactions on Intelligence Technology
Subjects:
regression analysis
mean square error methods
estimation theory
data handling
cumulative linear regression
statistical methods
imputation algorithm
linear regression technique
imputed variables
linear regression equation
imputation time
missing data handling
missing values
root-mean-square error
mean absolute error
coefficient of determination
Online Access:https://digital-library.theiet.org/content/journals/10.1049/trit.2019.0032

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https://digital-library.theiet.org/content/journals/10.1049/trit.2019.0032

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