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The exponentiated Weibull distribution is a convenient alternative to the generalized gamma distribution to model time‐to‐event data. It accommodates both monotone and nonmonotone hazard shapes, and flexible enough to describe data with wide ranging characteristics. It can also be used for regression analysis of time‐to‐event data. The maximum likelihood method is thus far the most widely used technique for inference, though there is a considerable body of research of improving the maximum likelihood estimators in terms of asymptotic efficiency. For example, there has recently been considerable attention on applying James–Stein shrinkage ideas to parameter estimation in regression models. We propose nonpenalty shrinkage estimation for the exponentiated Weibull regression model for time‐to‐event data. Comparative studies suggest that the shrinkage estimators outperform the maximum likelihood estimators in terms of statistical efficiency. Overall, the shrinkage method leads to more accurate statistical inference, a fundamental and desirable component of statistical theory.

This paper presents a general framework for planning a multipurpose robot which can be used in multiple fields (both civil and military). The framework shows the assembly of multiple sensors, mechanical arm, live video streaming and high range remote control and so on in a single robot. The planning problem is one of five fundamental challenges to the development of a real robotic system able to serve both purposes related to military and civil like live surveillance(both auto and manual), rescuing under natural disaster aftermath, firefighting, object picking, hazard like ignition, volatile gas detection, exploring underground mine or even terrestrial exploration. Each of the four other areas – hardware design, programming, controlling and artificial intelligence are also discussed.