Record Details

Estimation of the Average Yield of Cotton using Outlier Robust Geographically Weighted Regression Approach

Indian Agricultural Research Journals

View Archive Info
 
 
Field Value
 
Title Estimation of the Average Yield of Cotton using Outlier Robust Geographically Weighted Regression Approach
 
Creator Moury, Pramod Kumar
Ahmad, Tauqueer
Rai, Anil
Biswas, Ankur
Sahoo, Prachi Misra
Huddar, Mohammadsanaulla K.
 
Subject Crop cutting experiments; GCES; Geographically weighted regression; Outlier robust geographically weighted regression, Spatial non‑stationarity
 
Description The General Crop Estimation Survey (GCES) scheme requires a large number of Crop Cutting Experiments (CCEs) to be conducted to get a reliable estimate below the district level. However, conducting a large number of CCEs imposes a financial burden on Govt. agencies. Additionally, large-scale surveys like GCES often result in many outlier observations in the CCE data. To address this issue,this study was conducted to estimate the yield rate of cotton with a relatively fewer number of CCEs than the GCES scheme using the proposed Outlier Robust Geographically Weighted Regression (ORGWR) approach. Validation of the proposed methodology was done using the real CCE dataset of Amravati district for the 2012-13 agriculture year in Maharashtra. In this approach,the number of CCEs conducted for GCES scheme was reduced, and then this reduced number of the CCEs can be predicted using the proposed ORGWR approach. The predicted CCEs and the incomplete CCEs data are then combined to form a complete dataset. This complete dataset is used to calculate the crop yield accurately. The study conducted a comparison between the ORGWR approach and GCES methodology for estimating the average yield of cotton. The results showed that the ORGWR approach, when used with a lesser number of CCEs,yielded estimates that were almost equivalent to those obtained using the GCES methodology with the complete dataset. Moreover, the standard error of the estimate was reliable, indicating the validity of the results.
 
Publisher Indian Society of Agricultural Statistics (ISAS)
 
Date 2024-09-10
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier https://epubs.icar.org.in/index.php/JISAS/article/view/155781
10.56093/jisas.v78i2.1
 
Source Journal of the Indian Society of Agricultural Statistics; Vol. 78 No. 2 (2024); 81–87
0019-6363
 
Language eng
 
Relation https://epubs.icar.org.in/index.php/JISAS/article/view/155781/55599
 
Rights Copyright (c) 2024 Journal of the Indian Society of Agricultural Statistics