Goodness-of-fit tests in parametric regression based on the estimation of the error distribution

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Model checking for parametric single‐index models: a dimension reduction model‐adaptive approach (2016, methodology): “For MAVE, we suggest a Bayesian information criterion (BIC) type of criterion that is a modified version of that proposed by Wang and Yin (2008) of the form BICk = log ( RSSk n ) + log.n/k min.nhk, √ n/ , where RRSk is the residual sum of squares and k is the estimate of the dimension.”
Smooth Residual Bootstrap for Empirical Processes of Non‐parametric Regression Residuals (2009, methodology): “…(such as tests for equality of error distributions in different models) as well as to the tests suggested by Pardo-Fernandez et al. (2007) and Van Keilegom et al. (2008) (goodness-of-fit tests for the regression function that are based on empirical processes of residuals) is also discussed.”
An updated review of Goodness-of-Fit tests for regression models (2013, methodology): “2.2 and 2.3 to these general contexts (see Van Keilegom et al. 2008b).”
Specification tests in nonparametric regression (2008, background): “…in Akritas and Van Keilegom (2001), Van Keilegom and Veraverbeke (2002), Cheng (2004), Müller et al. (2004a,b), among others, whereas Dette et al. (2007), Neumeyer et al. (2006), Van Keilegom et al. (2007) and Pardo-Fernández et al. (2007) studied various testing problems under this model.”