simul.commonprob {bindata} | R Documentation |
Compute common probabilities of binary random variates generated by thresholding normal variates at 0.
simul.commonprob(margprob, corr=0, method="integrate", n1=10^5, n2=10)
margprob |
vector of marginal probabilities. |
corr |
vector of correlation values for normal distribution. |
method |
either |
n1 |
number of normal variates if method is |
n2 |
number of repetitions if method is |
The output of this function is used by rmvbin
. For all
combinations of marginprob[i]
, marginprob[j]
and
corr[k]
, the probability that both components of a normal
random variable with mean qnorm(marginprob[c(i,j)])
and
correlation corr[k]
are larger than zero is computed.
The probabilities are either computed by numerical integration of the multivariate normal density, or by Monte Carlo simulation.
For normal usage of rmvbin
it is not necessary to use
this function, one simulation result is provided as variable
SimulVals
in this package and loaded by default.
simul.commonprob
returns an array of dimension
c(length(margprob), length(margprob), length(corr))
.
Friedrich Leisch
Friedrich Leisch, Andreas Weingessel and Kurt Hornik (1998). On the generation of correlated artificial binary data. Working Paper Series, SFB “Adaptive Information Systems and Modelling in Economics and Management Science”, Vienna University of Economics.
simul.commonprob(seq(0,1,0.5), seq(-1,1,0.5), meth="mo", n1=10^4)
data(SimulVals)