A complementary study on analysis of simulation results using statistical models

Abstract

Simulation studies are often conducted when it is difficult to compare the performance of nonparametric es-timators theoretically. Kim and Kim (2021) showed that more systematic and accurate comparisons can be made if you analyze the simulation results using a regression model,. This study is a complementary study on Kim and Kim (2021). In the variance-covariance matrix for the error term of the regression model, only heteroscedasticity was considered and covariance was ignored in the previous study. When covariance is considered together with the heteroscedasticity, the variance-covariance matrix becomes a block diagonal matrix. In this study, a method of estimating and using the block diagonal variance-covariance matrix for the analysis was presented. This al-lows you to find more pairs of estimators with significant performance differences while ensuring the nominal confidence level.