  Cox proportional hazards model with measurement error is investigated. In
Kukush et al. (2011) [Journal of Statistical Research 45, 77-94] and Chimisov
and Kukush (2014) [Modern Stochastics: Theory and Applications 1, 13-32]
asymptotic properties of simultaneous estimator $\lambda_n(\cdot)$, $\beta_n$
were studied for baseline hazard rate $\lambda(\cdot)$ and regression parameter
$\beta$, at that the parameter set $\Theta=\Theta_{\lambda}\times
\Theta_{\beta}$ was assumed bounded. In the present paper, the set
$\Theta_{\lambda}$ is unbounded from above and not separated away from $0$. We
construct the estimator in two steps: first we derive a strongly consistent
estimator and then modify it to provide its asymptotic normality.
