tornado: Computes Correlation between Inputs and Output in a mc Object (tornado) in the Variability Dimension;

Description

Provides statistics for a tornado chart. Evaluates correlations between output and inputs of a mc object.

Usage

tornado(mc, output=length(mc), use="all.obs", method=c("spearman",
	  "kendall", "pearson"), lim=c(0.025, 0.975))
"print"(x, ...)

Arguments

a mc object or a mccut object.

A tornado object as provided by the tornado function.

output

(for mc objects only). The rank or the name of the output to be considered. By default: the last element of the mc.

use

(for mc objects only). An optional character string giving a method for computing covariances in the presence of missing values. This must be (an abbreviation of) one of the strings "all.obs", "complete.obs" or "pairwise.complete.obs" (see cor).

method

(for mc objects only). A character string indicating which correlation coefficient (or covariance) is to be computed. One of "spearman" (default), "kendall" or "pearson", can be abbreviated (see cor). Warning : the default is not the same in cor.

lim

A vector of quantiles used to compute the credible interval in two-dimensional models.

...

Further arguments to be passed to the final print function.

Value

An invisible object of class tornado. A tornado object is a list of objects containing the following objects:

Details

The tornado function computes the spearman's rho statistic. It is used to estimate a rank-based measure of association between one set of random variable of a mc object (the output) and the others (the inputs).

tornado may be applied on a mccut object if a tornado function was used in the third block of the evalmccut call.

If "output" refers to a "0" mcnode, it is an error. If "output" refers to a "V" mcnode, correlations are only provided for other "V" mcnodes. If "output" refers to a "U" mcnode, correlations are only provided for other "U" mcnodes. If "output" refers to a "VU" mcnode, correlations are only provided for other "VU" mcnodes and "V" mcnodes.

If use is "all.obs", then the presence of missing observations will produce an error. If use is "complete.obs" then missing values are handled by casewise deletion. Finally, if use has the value "pairwise.complete.obs" then the correlation between each pair of variables is computed using all complete pairs of observations on those variables.

Examples

Run this code

data(total)
tornado(total, 2, "complete.obs", "spearman", c(0.025, 0.975))
tornado(total, 4, "pairwise.complete.obs", "spearman", c(0.025, 0.975))
tornado(total, 6, "complete.obs", "kendall", c(0.025, 0.975))
tornado(total, 8, "complete.obs", "spearman", c(0.025, 0.975))
(y <- tornado(total, 10, "complete.obs", "spearman", c(0.025, 0.975)))
plot(y)