Consistent Nonparametric Entropy-Based Testing

By Peter M. Robinson. 1991

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Citations in the corpus

A Kernel Independence Test for Random Processes (2014, background): “…et al., 1996); criteria based on integrated squared distance between densities e.g (Rosenblatt & Wahlen, 1992); KL-divergence based criteria e.g. (Robinson, 1991; Hong & White, 2005); and generalizations of KL-divergence to so called q-class entropies 1We distinguish our case from the problem…”
Can Rare Events Explain the Equity Premium Puzzle (2008, unknown): “The reason behind the good asymptotic and nite sample properties of the empirical likelihood approach is that the KLIC, as pointed out by Robinson (1991), is extremely sensitive to any deviation of one probability measure from another.”
On the Kozachenko-Leonenko entropy estimator (2016, background): “Also, Robinson [15] proposed some independence test, based on the fact that f ⊗ g maximizes H(F ) among all distributions F with marginals f and g.”
Intrinsic credible regions: An objective Bayesian approach to interval estimation (2005, methodology): “This measure has been used to build a test of independence (Robinson, 1991), identifying lags in the relationship in nonlinear time series modeling (Granger and Lin, 1994) or building measures of general dependency among vector random variables (Peña and van der Linde, 2005), among others…”
Testing the Significance of Categorical Predictor Variables in Nonparametric Regression Models (2006, background): “the distribution is quite sensitive to bandwidth choice. For example, Robinson (1991)”
A Dependence Metric for Possibly Nonlinear Processes (2004, background): “literature; see Joe (1989), Robinson (1991) , Skaug & Tj?stheim (1996), and Granger & Lin (1994).”
A Non-Parametric Independence Test Using Permutation Entropy (2008, methodology): “It does not involve sample splitting (as Robinson (1991) requires) and thus, it does not need choosing tuning parameters that can lead to ambiguous conclusions when the test is used by two different practitioners.”
Characterizations of joint distributions, copulas, information, dependence and decoupling, with applications to time series (2006, background): “, Robinson [66], Granger and Lin [29] and Hong and White [31]) considered problems of estimating entropy measures of serial dependence in time”
A versatile and robust metric entropy test of time-reversibility, and other hypotheses (2007, methodology): “Under these assumptions proof of consistency of classes of measures, including S̃ρ, follows from Skaug & Tjøstheim (1993) and also Robinson (1991).”
Testing Conditional Independence via Rosenblatt Transforms (2009, background): “To name but a few, see Hoeffding (1948), Blum, Kiefer and Rosenblatt (1961), Skaug and Tjøstheim (1993), Robinson (1991), Delgado and Mora (2000) and Hong and White (2005).”
A nonparametric test for equality of distributions with mixed categorical and continuous data (2009, background): “paper see Robinson (1991) , as well as Hong & White (2000), Ahmad & Li (1997), and Racine”
A test for volatility spillover with application to exchange rates (2001, methodology): “Such a measure has been used in identifying possible lag structures of non-linear time series (e.g., Granger and Lin, 1994) and in hypothesis testing (e.g., Hong and White, 2001; Robinson, 1991).”
A NONPARAMETRIC HELLINGER METRIC TEST FOR CONDITIONAL INDEPENDENCE (2008, methodology): “Other statistics can be constructed using entropy (e.g., Robinson, 1991, Fernandes, 2000, Hong and”