Correlation Analysis of Multimodal Sensor Data in Environmental Sensor Networks

Abstract

In this paper, the performance analysis of the classical measures of correlation coefficients, i.e., Pearson's correlation coefficient r-{P}, Spearman's rank correlation coefficient, r-{S} and Kendall-\tau rank correlation coefficient, r-{K}, and four robust correlation coefficients, is carried out in a specific scenario of multimodal environmental sensor network. The correlation coefficients were compared based on their estimated values with true values calculated using the slope of the regression line of the data points. The analysis is performed for two typical multivariate environmental sensor network scenarios, viz, positive correlation and negative correlation. The simulation results shed light on the required sample size of multimodal data and the class of the correlation coefficient required to give the best performance while establishing the correlation between the multimodal variables in environmental sensor data. © 2019 IEEE.