Abstract
The literature on fixed effects panel interval-valued data models has been established. However, less attention has been given to models that simultaneously, consider the interval information of panel data and explore the nonlinear relationship between interval variables. To deal with this issue, this paper formulates a nonparametric fixed effects panel interval-valued data model. To estimate the fixed effects and nonparametric component, we propose a locally linear method based on the profile least squares framework. Later, experiment results on synthetic and real data sets illustrate the advantages of our proposed model.
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