Description Usage Arguments Value See Also Examples
Fitting of and simulation from a copula model.
1 2 3 
x 
a matrix or data frame of effectiveness scores to estimate dependence. 
eff 
a list of effectiveness distributions to use for the margins. 
... 
other parameters for 
n 
number of observations to simulate. 
.effcop 
the 
effcopFit
: an object of class effcop
, with the following components:
data  the matrix of effectiveness scores used to fit the copula. 
pobs  the matrix of pseudoobservations computed from data . This is stored
because pseudoobservations are calculated breaking ties randomly
(see pseudo_obs ). 
margins  the list of marginal effectiveness distributions. 
cop  the underlying copulas fitted with vinecop .

These components may be altered to gain specific simulation capacity, such as systems with the same expected value.
reffcop
: a matrix of random scores.
effCont
and effDisc
for available distributions for the
margins. See package rvinecopulib
for details on fitting
the copulas.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17  ## Automatically build a gaussian copula to many systems
d < web2010p20[,1:20] # sample P@20 data from 20 systems
effs < effDiscFitAndSelect(d, support("p20")) # fit and select margins
cop < effcopFit(d, effs, family_set = "gaussian") # fit copula
y < reffcop(1000, cop) # simulate new 1000 topics
# compare observed vs. expected mean
E < sapply(effs, function(e) e$mean)
E.hat < colMeans(y)
plot(E, E.hat)
abline(0:1)
# compare observed vs. expected variance
Var < sapply(effs, function(e) e$var)
Var.hat < apply(y, 2, var)
plot(Var, Var.hat)
abline(0:1)

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