@article{HirschfeldLustfeldReisseletal.2010,
  author    = {Hirschfeld, J. A. and Lustfeld, H. and Reißel, Martin and Steffen, B.},
  title     = {A novel scheme for precise diagnostics and effective stabilization of currents in a fuel cell stack},
  series = {International Journal of Energy Research. 34 (2010), H. 3},
  journal   = {International Journal of Energy Research. 34 (2010), H. 3},
  isbn      = {0363-907X},
  pages     = {293 -- 301},
  year      = {2010},
  language  = {en}
}
@article{HirschfeldLustfeldReisseletal.2010,
  author    = {Hirschfeld, J. A. and Lustfeld, H. and Reißel, Martin and Steffen, B.},
  title     = {Tomographic diagnostics of current distributions in a fuel cell stack},
  series = {International Journal of Energy Research},
  volume    = {34},
  journal   = {International Journal of Energy Research},
  number    = {3},
  isbn      = {0363-907X},
  pages     = {284 -- 292},
  year      = {2010},
  language  = {en}
}
@article{HafnerDemetzWeickertetal.2014,
  author    = {Hafner, David and Demetz, Oliver and Weickert, Joachim and Reißel, Martin},
  title     = {Mathematical Foundations and Generalisations of the Census Transform for Robust Optic Flow Computation},
  series = {Journal of Mathematical Imaging and Vision},
  journal   = {Journal of Mathematical Imaging and Vision},
  publisher = {Springer},
  address   = {New York},
  issn      = {1573-7683 (Online)},
  doi       = {10.1007/s10851-014-0529-9},
  year      = {2014},
  language  = {en}
}
@article{DiktaReisselHarlass2016,
  author    = {Dikta, Gerhard and Reißel, Martin and Harlaß, Carsten},
  title     = {Semi-parametric survival function estimators deduced from an identifying Volterra type integral equation},
  series = {Journal of multivariate analysis},
  journal   = {Journal of multivariate analysis},
  number    = {147},
  publisher = {Elsevier},
  address   = {Amsterdam},
  doi       = {10.1016/j.jmva.2016.02.008},
  pages     = {273 -- 284},
  year      = {2016},
  abstract  = {Based on an identifying Volterra type integral equation for randomly right censored observations from a lifetime distribution function F, we solve the corresponding estimating equation by an explicit and implicit Euler scheme. While the first approach results in some known estimators, the second one produces new semi-parametric and pre-smoothed Kaplan-Meier estimators which are real distribution functions rather than sub-distribution functions as the former ones are. This property of the new estimators is particular useful if one wants to estimate the expected lifetime restricted to the support of the observation time. Specifically, we focus on estimation under the semi-parametric random censorship model (SRCM), that is, a random censorship model where the conditional expectation of the censoring indicator given the observation belongs to a parametric family. We show that some estimated linear functionals which are based on the new semi-parametric estimator are strong consistent, asymptotically normal, and efficient under SRCM. In a small simulation study, the performance of the new estimator is illustrated under moderate sample sizes. Finally, we apply the new estimator to a well-known real dataset.},
  language  = {en}
}