  Cox proportional hazards model with measurement errors is considered. In
Kukush and Chernova (2017), we elaborated a simultaneous estimator of the
baseline hazard rate $\lambda(\cdot)$ and the regression parameter $\beta$,
with the unbounded parameter set
$\varTheta=\varTheta_{\lambda}\times\varTheta_{\beta}$, where
$\varTheta_{\lambda}$ is a closed convex subset of $C[0,\tau]$ and
$\varTheta_{\beta}$ is a compact set in $\mathbb{R}^m$. The estimator is
consistent and asymptotically normal. In the present paper, we construct
confidence intervals for integral functionals of $\lambda(\cdot)$ and a
confidence region for $\beta$ under restrictions on the error distribution. In
particular, we handle the following cases: (a) the measurement error is
bounded, (b) it is a normally distributed random vector, and (c) it has
independent components which are shifted Poisson random variables.
