Refine
Year of publication
Document Type
- Article (1578) (remove)
Keywords
- Einspielen <Werkstoff> (7)
- FEM (4)
- Finite-Elemente-Methode (4)
- LAPS (4)
- CellDrum (3)
- Label-free detection (3)
- biosensors (3)
- hydrogen peroxide (3)
- shakedown analysis (3)
- Bacillus atrophaeus (2)
- Bauingenieurwesen (2)
- CAD (2)
- Capacitive field-effect sensor (2)
- Einspielanalyse (2)
- Empirical process (2)
- Field-effect sensor (2)
- Goodness-of-fit test (2)
- Independence test (2)
- Light-addressable potentiometric sensor (2)
- Lipopolysaccharide (2)
Institute
- Fachbereich Medizintechnik und Technomathematik (1578) (remove)
We consider a binary multivariate regression model where the conditional expectation of a binary variable given a higher-dimensional input variable belongs to a parametric family. Based on this, we introduce a model-based bootstrap (MBB) for higher-dimensional input variables. This test can be used to check whether a sequence of independent and identically distributed observations belongs to such a parametric family. The approach is based on the empirical residual process introduced by Stute (Ann Statist 25:613–641, 1997). In contrast to Stute and Zhu’s approach (2002) Stute & Zhu (Scandinavian J Statist 29:535–545, 2002), a transformation is not required. Thus, any problems associated with non-parametric regression estimation are avoided. As a result, the MBB method is much easier for users to implement. To illustrate the power of the MBB based tests, a small simulation study is performed. Compared to the approach of Stute & Zhu (Scandinavian J Statist 29:535–545, 2002), the simulations indicate a slightly improved power of the MBB based method. Finally, both methods are applied to a real data set.