q.hit

A matrix that has time-series observations in its columns

DATA

A vector of probabilty values at which sample quantiles are estimated

vecA

Returns the matrix of quantil-hits

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

q.hit function

<dl><dt>DATA</dt>
<dd>A matrix that has time-series observations in its columns</dd>
<dt>vecA</dt>
<dd>A vector of probabilty values at which sample quantiles are estimated</dd></dl>

Arguments

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

Author

Quantile Hit — q.hit

<dl>

<dt>DATA</dt>
<dd>A matrix that has time-series observations in its columns</dd>


<dt>vecA</dt>
<dd>A vector of probabilty values at which sample quantiles are estimated</dd>

</dl>

q.hit: Quantile Hit

Description

Usage

Value

Arguments

Author

Details