An Improved Meta-analysis for Analyzing Cylindrical-type Time Series Data with Applications to Forecasting Problem in Environmental Study

• Main Author: Wang, Shuo
• Other Authors: Sungsu Kim, Advisor
• Format: Others
• Published: Digital WPI 2015
• Subjects: Time series; Meta-analysis; Covariance matrix; Generalized least square; Linear-circular regression
• Online Access: https://digitalcommons.wpi.edu/etd-theses/386; https://digitalcommons.wpi.edu/cgi/viewcontent.cgi?article=1385&context=etd-theses

This thesis provides a case study on how the wind direction plays an important role in the amount of rainfall, in the village of Somi$acute{o}$. The primary goal is to illustrate how a meta-analysis, together with circular data analytic methods, helps in analyzing certain environmental issues. The existing GLS meta-analysis combines the merits of usual meta-analysis that yields a better precision and also accounts for covariance among coefficients. But, it is quite limited since information about the covariance among coefficients is not utilized. Hence, in my proposed meta-analysis, I take the correlations between adjacent studies into account when employing the GLS meta-analysis. Besides, I also fit a time series linear-circular regression as a comparable model. By comparing the confidence intervals of parameter estimates, covariance matrix, AIC, BIC and p-values, I discuss an improvement on the GLS meta analysis model in its application to forecasting problem in Environmental study.