TY - JOUR A1 - Doll, T. A1 - Scharnagl, K. A1 - Winter, R. A1 - Bögner, M. A1 - Eisele, I. A1 - Ostrik, B. A1 - Schöning, Michael Josef T1 - Work function gas sensors - reference layers and signal analysis JF - Eurosensors XII : proceedings of the 12th European Conference on Solid-State Transducers and the 9th UK Conference on Sensors and their Applications, Southampton, UK, 13 - 16 September 1998 / ed. by N. M. White ; Vol. 1 Y1 - 1998 SN - 0-7503-0595-9 N1 - Eurosensors ; (12, 1998, Southampton) ; UK Conference on Sensors and Their Applications ; (9, 1998, Southampton) SP - 143 EP - 146 PB - Inst. of Physics Publ. CY - Bristol [u.a.] ER - TY - JOUR A1 - Ditzhaus, Marc A1 - Gaigall, Daniel T1 - A consistent goodness-of-fit test for huge dimensional and functional data JF - Journal of Nonparametric Statistics N2 - A nonparametric goodness-of-fit test for random variables with values in a separable Hilbert space is investigated. To verify the null hypothesis that the data come from a specific distribution, an integral type test based on a Cramér-von-Mises statistic is suggested. The convergence in distribution of the test statistic under the null hypothesis is proved and the test's consistency is concluded. Moreover, properties under local alternatives are discussed. Applications are given for data of huge but finite dimension and for functional data in infinite dimensional spaces. A general approach enables the treatment of incomplete data. In simulation studies the test competes with alternative proposals. KW - Cramér-von-Mises statistic KW - separable Hilbert space KW - huge dimensional data KW - functional data Y1 - 2018 U6 - https://doi.org/10.1080/10485252.2018.1486402 SN - 1029-0311 VL - 30 IS - 4 SP - 834 EP - 859 PB - Taylor & Francis CY - Abingdon ER - TY - JOUR A1 - Ditzhaus, Marc A1 - Gaigall, Daniel T1 - Testing marginal homogeneity in Hilbert spaces with applications to stock market returns JF - Test N2 - This paper considers a paired data framework and discusses the question of marginal homogeneity of bivariate high-dimensional or functional data. The related testing problem can be endowed into a more general setting for paired random variables taking values in a general Hilbert space. To address this problem, a Cramér–von-Mises type test statistic is applied and a bootstrap procedure is suggested to obtain critical values and finally a consistent test. The desired properties of a bootstrap test can be derived that are asymptotic exactness under the null hypothesis and consistency under alternatives. Simulations show the quality of the test in the finite sample case. A possible application is the comparison of two possibly dependent stock market returns based on functional data. The approach is demonstrated based on historical data for different stock market indices. Y1 - 2022 U6 - https://doi.org/10.1007/s11749-022-00802-5 SN - 1863-8260 VL - 2022 IS - 31 SP - 749 EP - 770 PB - Springer ER - TY - JOUR A1 - Dikta, Gerhard A1 - Subramanian, Sundarraman T1 - Inverse censoring weighted median regression / Sundarraman Subramanian and Gerhard Dikta JF - Statistical Methodology. 6 (2009), H. 6 Y1 - 2009 SN - 1572-3127 SP - 594 EP - 603 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Dikta, Gerhard A1 - Reißel, Martin A1 - Harlaß, Carsten T1 - Semi-parametric survival function estimators deduced from an identifying Volterra type integral equation JF - Journal of multivariate analysis N2 - 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. KW - Volterra integral equation KW - Product-integration KW - Asymptotic efficiency KW - Semi-parametric random censorship model KW - Censored data KW - Survival analysis Y1 - 2016 U6 - https://doi.org/10.1016/j.jmva.2016.02.008 IS - 147 SP - 273 EP - 284 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Dikta, Gerhard A1 - Kühlheim, René A1 - Mendonca, Jorge A1 - Una-Alcarez, Jacobo de T1 - Asymptotic representation of presmoothed Kaplan–Meier integrals with covariates in a semiparametric censorship model JF - Journal of Statistical Planning and Inference Y1 - 2015 U6 - https://doi.org/10.1016/j.jspi.2015.12.001 SN - 0378-3758 VL - Vol. 171 SP - 10 EP - 37 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Dikta, Gerhard A1 - Kvesic, Marsel A1 - Schmidt, Christian T1 - Bootstrap Approximations in Model Checks for Binary Data JF - Journal of the American Statistical Association. 101 (2006), H. 474 Y1 - 2006 SN - 0162-1459 SP - 521 EP - 530 ER - TY - JOUR A1 - Dikta, Gerhard A1 - Kurtz, B. A1 - Stute, W. T1 - Sequential Fixed-Width Confidence Bands for Distribution Functions Under Random Censoring JF - Metrika. 36 (1989) Y1 - 1989 SN - 0026-1335 SP - 167 EP - 176 ER - TY - JOUR A1 - Dikta, Gerhard A1 - Hausmann, Rolf A1 - Schmidt, Christian T1 - Some Simulation Results under Random Censorship Models Y1 - 2002 N1 - gesehen 18.06.2007 SP - 1 EP - 12 ER - TY - JOUR A1 - Dikta, Gerhard A1 - Ghorai, Jugal A1 - Schmidt, Christian T1 - The Central Limit Theorem under Semiparametric Random Censorship Models JF - Journal of Statistical Planning and Inference. 127 (2005), H. 1 Y1 - 2005 SN - 0378-3758 SP - 23 EP - 51 ER -