TY  - JOUR
A1  - Heel, Mareike van
A1  - Dikta, Gerhard
A1  - Braekers, Roel
T1  - Bootstrap based goodness‑of‑fit tests for binary multivariate regression models
T2  - Journal of the Korean Statistical Society
N2  - 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.
Y1  - 2021
UR  - https://opus.bibliothek.fh-aachen.de/opus4/frontdoor/index/index/docId/9698
SN  - 2005-2863 (Online)
SN  - 1226-3192 (Print)
N1  - Corresponding author: Mareike van Heel
VL  - 51
PB  - Springer Nature
CY  - Singapur
ER  -