Under independent <right censoring>, observation $(x_i,d_i)$ contributes
$$
f(x_i;\eta)^{d_i}S(x_i;\eta)^{1-d_i}
=h(x_i;\eta)^{d_i}S(x_i;\eta),
$$
where $d_i$ indicates an event. Multiply these contributions, take the <log-likelihood>, and maximize it over the parametric survival-model parameter $\eta$, numerically if the score equations have no closed form.

Solution

Past exam of the mathematics course of the University of Cambridge / 2025 / iii / Paper 207 / 5 / a / Solution

 Solution

ID: past-exam-of-the-mathematics-course-of-the-university-of-cambridge/2025/iii/paper-207/5/a/solution