dCovTS (version 1.0)

mADCFplot: Distance cross-correlation plot

Description

The function computes and plots the estimator of the distance correlation matrix mADCF.

Usage

mADCFplot(x, MaxLag = 15, ylim= NULL, b = 499)

Arguments

x

multivariate time series.

MaxLag

maximum lag order at which to plot mADCF. Default is 15.

ylim

numeric vector of length 2 indicating the y limits of the plot. The default value, NULL, indicates that the range $(0,v)$, where $v$ is the maximum number between 1 and the empirical critical values, should be used.

b

the number of Wild bootstrap replications for constructing the 95% empirical confidence intervals. Default is 499.

Value

A plot of the estimated mADCF matrices. The function also returns a list with

matrices

Sample distance correlation matrices starting from lag 0.

critical.value

The critical value shown in the plot.

Details

The 95% confidence intervals shown in the plot (dotted blue horizontal line) are computed simultaneously based on the Independent Wild Bootstrap approach (Shao, 2010; Leucht and Neumann, 2013), since the elements of mADCV (and thus mADCF) can be expressed as degenerate V-statistics of order 2. More details can be found in Fokianos and Pitsillou (2016).

References

Fokianos K. and M. Pitsillou (2016). On multivariate auto-distance covariance and correlation functions. Submitted for publication.

Leucht, A. and M. H. Neumann (2013). Dependent wild bootstrap for degenerate U- and V- statistics. Journal of Multivariate Analysis $\textbf{117}$, 257-280, http://dx.doi.org/10.1016/j.jmva.2013.03.003.

Shao, X. (2010). The dependent wild bootstrap. Journal of the American Statistical Association $\textbf{105}$, 218-235, http://dx.doi.org/10.1198/jasa.2009.tm08744.

See Also

mADCF, mADCV

Examples

x <- MASS::mvrnorm(100,rep(0,3),diag(3))
## Not run: mADCFplot(x,18,ylim=c(0,0.5))
y <- MASS::mvrnorm(100,rep(0,6),diag(6))
## Not run: mADCFplot(y,b=100)

deaths <- cbind(mdeaths,fdeaths)
## Not run: mADCFplot(deaths)