A Three-Stage Nonparametric Kernel-Based Time Series Model Based on Fuzzy Data

In this paper, a nonlinear time series model is developed for the case when underlying data are reported by LR fuzzy numbers. To end, we present three-stage nonparametric kernel-based estimation procedure center as well left and right spreads of unknown smooth function. each stage, Nadaraya–Watson estimator used to evaluate A hybrid algorithm proposed estimate optimal bandwidths autoregressive order simultaneously. Various goodness-of-fit measures utilized performance assessment comparative analysis. The practical applicability superiority novel approach in comparison with further models demonstrated via simulation study some real-life applications.