Statistics & Risk Modeling
with Applications in Finance and Insurance
Editor-in-Chief: Stelzer, Robert
4 Issues per year
Cite Score 2017: 0.96
SCImago Journal Rank (SJR) 2017: 0.455
Source Normalized Impact per Paper (SNIP) 2017: 0.853
Mathematical Citation Quotient (MCQ) 2017: 0.32
On nonparametric estimation of the regression function under random censorship model
In this paper, we study the behavior of a kernel estimator for the regression function in a random right-censoring model. We establish pointwise and uniform strong consistency over a compact set and give a rate of convergence for the estimate.The asymptotic normality of the estimate is also proved. Simulations are drawn for different cases to illustrate both, convergence and asymptotic normality.
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