Kernel regression estimation for LTRC and associated data. (English) Zbl 07720162
Summary: This paper focuses on nonparametric regression modeling of time-series and incomplete observations. In this sense, the observations are subject to both left truncation and right censoring (LTRC) and satisfy an association dependency. Using the well-known kernel estimation method, we establish the strong uniform consistency with a rate of the kernel estimator proposed in this paper. Simulation studies are conducted to assess the impact of both incompleteness and association dependency on the estimation.
Keywords:
association; kernel regression; optimal bandwidth; strong uniform consistency rate; truncated-censored dataReferences:
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