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We propose two new kernel-type estimators of the mean residual life function$m_X(t)$ of bounded or half-bounded interval supported distributions. Thoughnot as severe as the boundary problems in the kernel density estimation,eliminating the boundary bias problems that occur in the naive kernel estimatorof the mean residual life function is needed. In this article, we utilize theproperty of bijective transformation. Furthermore, our proposed methodspreserve the mean value property, which cannot be done by the naive kernelestimator. Some simulation results showing the estimators' performances and areal data analysis will be presented in the last part of this article.

Boundary-free Estimators of the Mean Residual Life Function by Transformation