@article{HaselgruberMautnerThiele2010,
  author    = {Haselgruber, Nikolaus and Mautner, Karin and Thiele, Jan},
  title     = {Usage Space Analysis for Reliability Testing},
  series = {Quality and Reliability Engineering International},
  volume    = {26},
  journal   = {Quality and Reliability Engineering International},
  number    = {8},
  publisher = {Wiley},
  address   = {New York},
  issn      = {1099-1638},
  doi       = {10.1002/qre.1155},
  pages     = {877 -- 885},
  year      = {2010},
  abstract  = {During the development process of a complex technical product, one widely used and important technique is accelerated testing where the applied stress on a component is chosen to exceed the reference stress, i.e. the stress encountered in field operation, in order to reduce the time to failure. For that, the reference stress has to be known. Since a complex technical product may fail regarding numerous failure modes, stress in general is highly dimensional rather than scalar. In addition, customers use their products individually, i.e. field operation should be described by a distribution rather than by one scalar stress value. In this paper, a way to span the customer usage space is shown. It allows the identification of worst case reference stress profiles in significantly reduced dimensions with minimal loss of information. The application example shows that even for a complex product like a combustion engine, stress information can be compressed significantly. With low measurement effort it turned out that only three reference stress cycles were sufficient to cover a broad range of customer stress variety.},
  language  = {en}
}
@article{BaringhausGaigallThiele2018,
  author    = {Baringhaus, Ludwig and Gaigall, Daniel and Thiele, Jan Philipp},
  title     = {Statistical inference for L²-distances to uniformity},
  series = {Computational Statistics},
  volume    = {2018},
  journal   = {Computational Statistics},
  number    = {33},
  publisher = {Springer},
  address   = {Berlin},
  issn      = {1613-9658},
  doi       = {10.1007/s00180-018-0820-0},
  pages     = {1863 -- 1896},
  year      = {2018},
  abstract  = {The paper deals with the asymptotic behaviour of estimators, statistical tests and confidence intervals for L²-distances to uniformity based on the empirical distribution function, the integrated empirical distribution function and the integrated empirical survival function. Approximations of power functions, confidence intervals for the L²-distances and statistical neighbourhood-of-uniformity validation tests are obtained as main applications. The finite sample behaviour of the procedures is illustrated by a simulation study.},
  language  = {en}
}