Description Usage Arguments Details Value Author(s) References See Also Examples
Compute multivariate conditional Spearman's rho over a range of quantiles.
1 2 3 4 5 6 7 8 9 10  MCS(X, p = seq(0.1, 0.9, by = 0.1))
bootMCS(X, p = seq(0.1, 0.9, by = 0.1), R = 100, trace = 10)
## S3 method for class 'MCS'
plot(x, xlab="p", ylab="MCS", ...)
## S3 method for class 'bootMCS'
summary(object, alpha=0.05, ...)
## S3 method for class 'bootMCS'
plot(x, xlab="p", ylab="MCS", alpha=0.05, ylim, ...)

X 
A matrix of numeric variables. 
p 
The quantiles at which to evaluate. 
R 
The number of bootstrap samples to run. Defaults to

trace 
How often to inform the user of progress. Defaults to

x, object 
An object of class 
xlab, ylab 
Axis labels. 
alpha 
A (1  alpha)% pointwise confidence interval will be produced.
Defaults to 
ylim 
Plotting limits for bootstrap plot. 
... 
Optional arguments to be passed into methods. 
The method is described in detail by Schmid and Schmidt (2007). The main code was written by Yiannis Papastathopoulos, wrappers written by Harry Southworth.
When the result of a call to bootMCS
is plotted, simple
quantile bootstrap confidence intervals are displayed.
MCS returns an object of class MCS
. There are plot and summary methods available for this class.
MCS 
The estimated correlations. 
p 
The quantiles at which the correlations were evaluated at 
call 
The function call used. 
bootMCS returns an object of class bootMCS
. There are plot and summary methods available for this class.
replicates 
Bootstrap replicates. 
p 
The quantiles at which the correlations were evaluated at 
R 
Number of bootstrap samples. 
call 
The function call used. 
Yiannis Papastathopoulos, Harry Southworth
F. Schmid and R. Schmidt, Multivariate conditional versions of Spearman's rho and related measures of tail dependence, Journal of Multivariate Analysis, 98, 1123 – 1140, 2007
1 2 3 4 5 6 
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.