= Solution
The transformed event time is unit exponential, and the transformed censoring time remains a censoring time because $H$ is increasing. Under <independent censoring> and a correctly fitted model, the <Kaplan–Meier estimator> of the <survivor function> for the <Cox–Snell residuals> $\widehat H(x_i)$ should approximate $e^{-u}$.
Thus \b[a logarithmic survivor plot should follow a straight line through the origin with slope minus one]:
$$
\boxed{\log\widehat F_{\mathrm{res}}(u)\approx-u.}
$$
The empirical plot is a step function around that line. Systematic curvature suggests model misspecification; the late part is less stable when the <risk set> is small. The retained event indicators $v_i$ must be used rather than treating censored residuals as complete event times.
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