corr.lag

The matrix with the column size of 2

matH

The correlation statistics for a given lag order

Estimation and inference methods for the cross-quantilogram.
The cross-quantilogram is a measure of nonlinear dependence between
two variables, based on either unconditional or conditional quantile
functions. The cross-quantilogram can be considered as an extension
of the correlogram, which is a correlation function over multiple lag
periods and mainly focuses on linear dependency. One can use the
cross-quantilogram to detect the presence of directional
predictability from one time series to another. This package provides
a statistical inference method based on the stationary bootstrap. See
Linton and Whang (2007) <doi:10.1016/j.jeconom.2007.01.004> for
univariate time series analysis and Han, Linton, Oka and Whang (2016)
<doi:10.1016/j.jeconom.2016.03.001> for multivariate time series
analysis.

Tatsushi Oka

quantilogram

Cross-Quantilogram

Heejon Han

Oliver Linton

Yoon-Jae Whang

corr.lag function

<dl><dt>matH</dt>
<dd>The matrix with the column size of 2</dd>
<dt>k</dt>
<dd>The lag order (integer)</dd></dl>

Arguments

Heejoon Han, Oliver Linton, Tatsushi Oka and Yoon-Jae Whang

Author

Correlation Function — corr.lag

<dl>

<dt>matH</dt>
<dd>The matrix with the column size of 2</dd>


<dt>k</dt>
<dd>The lag order (integer)</dd>

</dl>

corr.lag: Correlation Function

Description

Usage

Value

Arguments

Author

Details