Analysis of Incomplete Data Under Different Missingness Mechanism using Imputation Methods for Wheat Genotypes-Reference-Cited by-同舟云学术

Analysis of Incomplete Data Under Different Missingness Mechanism using Imputation Methods for Wheat Genotypes

Published:2024-01-05 Issue:3 Volume:11 Page:1050-1056
ISSN:2321-9971
Container-title:Current Agriculture Research Journal
language:en
Short-container-title:Curr Agri Res Jour

Author:

Sanju Sanju¹,Kumar Vinay¹

Affiliation:

1. Department of Mathematics and Statistics, College of Basic Science and Humanities, CCS HAU, Hisar, Haryana, India.

Abstract

Missing values is a persistent problem in analysis of agriculture data. To improve the quality of the data in the agriculture study, imputation has drawn a lot of research interest. Non-missing data was removed with varying frequency from the genotypic data of the wheat crop by different missingness mechanism. Imputation methods namely last observation carried forward, mean, regression and KNN are applied to these data sets and compared their parameter with the parameter of original data. The performances of imputation methods are also evaluated by root mean square error for solving missing values at different missingness mechanism.

Publisher

Enviro Research Publishers

Subject

Pharmacology (medical)

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