A consistent nonparametric test for serial independence

By Joris Pinkse. 1998

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Citations in the corpus

A Kernel Independence Test for Random Processes (2014, methodology): “Pinkse (1998); Diks & Panchenko (2005) provide a quadratic forms function-based serial dependence test which employs the same statistic as HSIC.”
A Consistent Characteristic-Function-Based Test for Conditional Independence (2003, methodology): “…obtaining a computationally convenient test, based on limiting normal or chi-squared distributions, as in Hong (1999) or Brett and Pinkse (1997) and Pinkse (1998, 2000), who use characteristic function-based approaches to test for independence, serial independence, and spatial independence; and…”
DIAGNOSTIC CHECKING FOR THE ADEQUACY OF NONLINEAR TIME SERIES MODELS (2003, background): “…function in time series analysis ~e+g+, Epps, 1987, 1988; Feuerverger, 1990; Jiang and Knight, 2002; Knight and Satchell, 1997; Knight and Yu, 2002; Pinkse, 1998; Singleton, 2001!+ 6+ In a not unrelated context, Priestley~1988, p+ 143! discusses the physical interpretation of frequencyv…”
A Non-Parametric Independence Test Using Permutation Entropy (2008, background): “Needless to say that other nonparemetric tests have emerged (Brock et al. (1996) and Pinkse (1998), among others) to cover these difficulties.”
Generalized Spectral Tests for Conditional Mean Models in Time Series with Conditional Heteroscedasticity of Unknown Form (2005, background): “There has been an increasing interest in using the characteristic function in econometrics (e.g. Epps (1987, 1988), Pinkse (1998), Singleton (2001), Jiang and Knight (2002), Knight and Yu (2002), and Chacko and Viceira (2003)).”
An Updated Literature Review of Distance Correlation and Its Applications to Time Series (2017, unknown): “…or lag order and k ( ) is a Lipschitz-continuouskernel function with the following properties: ] is symmetric and is continuous at 0 and all but a ﬁnite number of points, with Distance measures obtained by characteristics functions have been also considered by Pinkse (1998) and Hong (1999).”
ASYMPTOTIC DISTRIBUTION THEORY FOR NONPARAMETRIC ENTROPY MEASURES OF SERIAL DEPENDENCE (2005, methodology): “Besides smoothed density estimators, alternative tools are correlation integrals, empirical distribution functions, and empirical characteristic functions (Brock, Dechert, Scheinkman, and LeBaron (1996), Delgado (1996), Hong (1998, 1999), Pinkse (1998), Skaug and Tjostheim (1993b)).”