Conference Program Home
  My Program

All Times EDT

Abstract Details

Activity Number: 277 - SPEED: Biometrics and Environmental Statistics Part 1
Type: Contributed
Date/Time: Tuesday, August 9, 2022 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics and the Environment
Abstract #322738
Title: Spatial Classification in the Presence of Measurement Error
Author(s): Yuhan Ma* and Kyuhee Shin and GyuWon Lee and Joon Jin Song
Companies: Baylor University and Kyungpook National University and Kyungpook National University and Baylor Univeristy
Keywords: Validation data; Misclassification; Multiple Imputation; Regression Calibration; Spatial Classification; Indicator Kriging

Spatial classification has received considerable attention in recent decades. In practice, the binary response variable is often subject to measurement error, misclassification. To account for the misclassified response in spatial classification, we proposed validation data-based adjustment methods using interval validation data. Regression calibration and multiple imputation methods are utilized to correct the misclassified responses at the locations where the gold-standard device not available. Generalized linear mixed model and indicator Kriging are applied for spatial prediction at unsampled locations. We perform simulation studies to compare the proposed methods with naïve methods that ignore the misclassification. It is found that the proposed models significantly improve predication accuracy. Additionally, we apply the proposed models for predicting the precipitation area in South Korea.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2022 program