Reliability of Essay Rating and Score Adjustment

1994 ◽  
Vol 19 (3) ◽  
pp. 171-200 ◽  
Author(s):  
N. T. Longford
Keyword(s):  
Mean Squared Error ◽  
Generalizability Theory ◽  
Diagnostic Procedures ◽  
Variance Component Model ◽  
Additive Variance ◽  
Error Estimators ◽  
Minimum Mean Squared Error ◽  
Rater Severity ◽  
Variance Homogeneity ◽  
Educational Tests

A model-based approach to rater reliability for essays read by multiple readers is presented. The approach is motivated by the generalizability theory. Variation of rater severity (between-rater variation) and rater inconsistency (within-rater variation) is considered in the presence of between-examinee variation. An additive variance component model is posited and the method of moments for its estimation described. The models involve no distributional assumptions other than variance homogeneity and independence of certain random variables. Minimum mean squared error estimators of examinees’ true scores and readers’ severities are derived. Model diagnostic procedures are an integral component of the approach. The methods are illustrated on data from standardized educational tests.

Minimum mean-squared-error estimators for simulation experiments

1981 ◽  
Vol 24 (4) ◽  
pp. 253-259 ◽  
Author(s):  
James H. Donnelly ◽  
Robert E. Shannon
Keyword(s):  
Mean Squared Error ◽  
Simulation Experiments ◽  
Error Estimators ◽  
Minimum Mean Squared Error ◽  
Squared Error

Multi-AUV Aided Cooperative 3D-localization for Underwater Sensor Networks

2020 ◽  
Vol 13 (1) ◽  
pp. 80-90 ◽  
Author(s):  
Meiyan Zhang ◽  
Wenyu Cai
Keyword(s):  
Sensor Networks ◽  
Mean Squared Error ◽  
Autonomous Underwater Vehicles ◽  
Estimation Method ◽  
Location Estimation ◽  
Underwater Sensor Networks ◽  
Coverage Ratio ◽  
Minimum Mean Squared Error ◽  
3D Localization ◽  
Localization Scheme

Background: Effective 3D-localization in mobile underwater sensor networks is still an active research topic. Due to the sparse characteristic of underwater sensor networks, AUVs (Autonomous Underwater Vehicles) with precise positioning abilities will benefit cooperative localization. It has important significance to study accurate localization methods. Methods: In this paper, a cooperative and distributed 3D-localization algorithm for sparse underwater sensor networks is proposed. The proposed algorithm combines with the advantages of both recursive location estimation of reference nodes and the outstanding self-positioning ability of mobile AUV. Moreover, our design utilizes MMSE (Minimum Mean Squared Error) based recursive location estimation method in 2D horizontal plane projected from 3D region and then revises positions of un-localized sensor nodes through multiple measurements of Time of Arrival (ToA) with mobile AUVs. Results: Simulation results verify that the proposed cooperative 3D-localization scheme can improve performance in terms of localization coverage ratio, average localization error and localization confidence level. Conclusion: The research can improve localization accuracy and coverage ratio for whole underwater sensor networks.

scholarly journals Attack-resilient minimum mean-squared error estimation

2014 ◽  
Author(s):  
James Weimer ◽  
Nicola Bezzo ◽  
Miroslav Pajic ◽  
Oleg Sokolsky ◽  
Insup Lee
Keyword(s):  
Error Estimation ◽  
Mean Squared Error ◽  
Minimum Mean Squared Error ◽  
Squared Error
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