Minimization of Negative Log Partial Likelihood Function Using Reproducing Kernel Hilbert Space

Nur'azah Abdul Manaf, Ibragimov Gafurjan, Mohd. Rizam Abu Bakar


Reproducing kernel Hilbert space (RKHS) can be used to estimate values of functions, derivatives and integrals of models. The RKHS kernels are useful in finding the optimizer  of the general Cox regression model. The procedure in the minimization of the negative log partial likelihood function is being demonstrated in this paper. Partial differentiation of the loss function is performed to determine the optimal values of .

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