Model Checks for Generalized Linear Models

By Winfried Stute, Lixing Zhu. 2002

143 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/5f72073fdabb4b65a94a34725f7a050bd819e9c4

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In Statistics and Probability

Citations in the corpus

Model Checks Using Residual Marked Empirical Processes (2004, unknown): “, (2π) −1/2 ∫ exp(iz(x − It−1))w(It−1, x)Ψ(dx) := Kw,Ψ(z), and therefore, by Parseval’s identity, see Taylor and Lay’s (1979) Theorem 6.”
Nonparametric checks for single-index models (2005, methodology): “M R1614600 [36] Stute,W .,T hies,S.and Zhu,L.-”
Model checking for parametric single‐index models: a dimension reduction model‐adaptive approach (2016, methodology): “We also make a comparison with Stute and Zhu’s (2002) test, because it works well in this scenario. The comparison can be used to examine whether and how much our test loses in power. In study 2, we compare our test with Stute and Zhu’s (2002) test to show that our test is omnibus whereas Stute and ”
An updated review of Goodness-of-Fit tests for regression models (2013, unknown): “For instance, Stute and Zhu (2005a) propose a scoretype test for H0SIM, which detects Pitman alternatives at a √ n-rate, and also peak alternatives, being undetectable for the previous tests, as discussed in Horowitz and Spokoiny (2001).”
Distribution free specification tests of conditional models (2008, methodology): “The random design case with a possibly nonlinear regression function has been dealt with in Stute et al. (1998), while applications to time series and generalized linear models may be found in Koul and Stute (1999) and Stute and Zhu (2002).”
Empirical likelihood confidence regions in a partially linear single‐index model (2006, methodology): “As a by-product, this bias correction also sheds light on the nonparametric estimation procedure for model checking because, when √ n-consistency is needed, we often need undersmoothing (see Chen et al. (2003), Stute and Zhu (2002, 2005), Zhu (2003) and Zhu and Ng (2003)).”
A Lack-of-Fit Test for Quantile Regression (2003, background): “A related approach was proposed by Bierens and Ploberger (1997), Stute, Thies, and Zhu (1998), Stute and Zhu (2002), and Zhu (2003).”