Muhammad Nur Aldi
Department of Statistics and Data Science, School of Data Science, Mathematics, and Informatics, IPB University

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Comparison of Ordinary Kriging and Cokriging for Spatial Estimation Based on Simulated Data Siti Mutiah; Muhammad Nur Aldi; Asep Saefuddin; Fitrah Ernawati
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 2 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v10i2.33409

Abstract

This study compares the performance of Ordinary Kriging (OK) and Cokriging (CK) methods in spatial estimation based on simulated data. Twelve scenarios are arranged based on a combination of sample size (50, 250, 500) and correlation levels between variables (ρ=0.1, 0.6, 0.9), with each scenario repeated 30 times. Spatial data are generated randomly within the geographical boundaries of Indonesia, variables are generated based on spherical variograms with nugget or sill or  dan range or ,, and model evaluation is carried out using Leave-One-Out Cross Validation (LOOCV) with RMSE and  metrics. The results show that Cokriging consistently produces more accurate estimates than Ordinary Kriging in all scenarios. In the best configuration (CK, n=500), RMSE = 1.04 and  = 0.945 were obtained, while the best performance of OK only reached RMSE = 1.06 and  = 0.873. All levels of correlation in Cokriging showed good performance, especially when the amount of data is sufficient. Therefore, Cokriging is recommended as a superior spatial interpolation method in the context of multivariate and spatial data, especially when relevant secondary information is available.