  One-shot devices data represent an extreme case of interval censoring.Some
kind of one-shot units do not get destroyed when tested, and so, survival units
can continue within the test providing extra information about their lifetime.
Moreover, one-shot devices may last for long times under normal operating
conditions, and so accelerated life tests (ALTs) may be used for inference.
ALTs relate the lifetime distribution of an unit with the stress level at which
it is tested via log-linear relationship.Then, mean lifetime of the devices are
reduced during the test by increasing the stress level and inference results on
increased stress levels can be easily extrapolated to normal operating
conditions. In particular, the step-stress ALT model increases the stress level
at pre-fixed times gradually during the life-testing experiment, which may be
specially advantageous for non-destructive one-shot devices. However, when the
number of units under test are few, outlying data may greatly influence the
parameter estimation. In this paper, we develop robust restricted estimators
based on the density power divergence (DPD) under linearly restricted
subspaces, for non-destructive one-shot devices under the step-stress ALTs with
exponential lifetime distributions. We theoretically study the asymptotic and
robustness properties of the restricted estimators and we empirically
illustrate such properties through a simulation study.
