Description Usage Arguments Details Value See Also Examples
View source: R/tornadounc.mc.R
Provides statistics for a tornado chart. Evaluates correlations between output and inputs of a mc object in the uncertainty dimension.
1 2 3 4 5 6 7 8 9 10  ## S3 method for class 'mc'
tornadounc(mc, output=length(mc), quant=c(0.5, 0.75, 0.975), use="all.obs",
method=c("spearman", "kendall", "pearson"), ...)
## Default S3 method:
tornadounc(mc, ...)
## S3 method for class 'tornadounc'
print(x, ...)
## S3 method for class 'mccut'
tornadounc(mc, output=length(mc), quant=c(0.5, 0.75, 0.975), use="all.obs",
method=c("spearman", "kendall", "pearson"), ...)

mc 
a mc object. 
x 
a tornadounc object. 
output 
The rank or the name of the output to be considered. Should be a "VU" or a "U" type mcnode. By default: the last element of mc. 
quant 
The vector of quantiles used in the variability dimension. 
use 
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 
method 
A character string indicating which correlation
coefficient (or covariance) is to be computed. One of "spearman"
(default), "kendall" or "pearson", can be abbreviated (see

... 
Further arguments to be passed to the final print function. 
The tornadounc.mc function computes the spearman's rho statistic between
values ("U" type mcnode) or statistics calculated in the variability dimension ("VU" type mcnode) of inputs and
values ("U" type mcnode) or statistics calculated in the variability dimension ("VU" type mcnode) of one output.
The statistics are the mean, the median and the quantiles specified by quant.
It is useful to estimate a rankbased measure of association between one set of random variable of a mc object (the output) and the others in the uncertainty dimension.
tornadounc.mccut may be applied on a mccut
object if a summary.mc function was used in the third block of
the evalmccut
call.
If output refers to a "0" or "V" mcnode, it is an error.
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.
An invisible object of class tornadounc. A tornadounc object is a list of objects containing the following objects:
value 
a matrix of values of correlation coefficients. Each row are the value or the statistics of inputs, each columns the value or the statistics of outputs. 
output 
the name of the output 
method 
the method used 
use 
the use parameter 
cor
.
tornado
for tornado in the variability dimension.
plot.tornadounc
to draw the results.
1 2 3 4 5 6 7  data(total)
tornadounc(total, 3)
tornadounc(total, 4, use="complete")
tornadounc(total, 7, use="complete.obs")
tornadounc(total, 8, use="complete.obs")
(y < tornadounc(total, 10, use="complete.obs"))
plot(y, 1, 1)

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