AbstractIn Huang (2010) [8], a test of conditional independence based on maximal nonlinear conditional correlation is proposed and the asymptotic distribution for the test statistic under conditional independence is established for IID data. In this paper, we derive the asymptotic distribution for the test statistic under conditional independence for α-mixing data. The results of simulation show that the test performs reasonably well for dependent data. We also apply the test to stock index data to test Granger noncausality between returns and trading volume
This paper proposes a new nonparametric test for conditional independence, which is based on the co...
Cataloged from PDF version of article.Maximal correlation has several desirable properties as a meas...
We propose information theoretic tests for serial independence and linearity in time series. The tes...
AbstractIn Huang (2010) [8], a test of conditional independence based on maximal nonlinear condition...
This paper proposes a nonparametric test of conditional independence based on the notion that two co...
Y is conditionally independent of Z given X if Pr{f(y|X, Z) =f(y|X)} =1for all y on its support, whe...
Y is conditionally independent of Z given X if Pr{f(y vertical bar X, Z) =f(y vertical bar X)} = 1 f...
We propose a characteristic function based test for conditional independence, which is applicable in...
Maximal correlation has several desirable properties as a measure of dependence, including the fact ...
This paper proposes a new statistic to test independence between two high dimensional random vectors...
We propose information theoretic tests for serial independence and linearity in time series against ...
Let f(y|x,z) (resp. f(y|x) be the conditional density of Y given (X,Z) (resp. X). We construct a cla...
Financial support from the Natural Sciences and Engineering Research Council of Canada and from the...
<p>Statistical inference on conditional dependence is essential in many fields including genetic ass...
It is a common saying that testing for conditional independence, i.e., testing whether whether two r...
This paper proposes a new nonparametric test for conditional independence, which is based on the co...
Cataloged from PDF version of article.Maximal correlation has several desirable properties as a meas...
We propose information theoretic tests for serial independence and linearity in time series. The tes...
AbstractIn Huang (2010) [8], a test of conditional independence based on maximal nonlinear condition...
This paper proposes a nonparametric test of conditional independence based on the notion that two co...
Y is conditionally independent of Z given X if Pr{f(y|X, Z) =f(y|X)} =1for all y on its support, whe...
Y is conditionally independent of Z given X if Pr{f(y vertical bar X, Z) =f(y vertical bar X)} = 1 f...
We propose a characteristic function based test for conditional independence, which is applicable in...
Maximal correlation has several desirable properties as a measure of dependence, including the fact ...
This paper proposes a new statistic to test independence between two high dimensional random vectors...
We propose information theoretic tests for serial independence and linearity in time series against ...
Let f(y|x,z) (resp. f(y|x) be the conditional density of Y given (X,Z) (resp. X). We construct a cla...
Financial support from the Natural Sciences and Engineering Research Council of Canada and from the...
<p>Statistical inference on conditional dependence is essential in many fields including genetic ass...
It is a common saying that testing for conditional independence, i.e., testing whether whether two r...
This paper proposes a new nonparametric test for conditional independence, which is based on the co...
Cataloged from PDF version of article.Maximal correlation has several desirable properties as a meas...
We propose information theoretic tests for serial independence and linearity in time series. The tes...