simul.commonprob {bindata} | R Documentation |
Compute common probabilities of binary random variates generated by
thresholding normal variates at 0. 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
CommonProb
in this package and loaded by default.
simul.commonprob(margprob, corr=0, method="integrate", n1=10^5, n2=10) data(CommonProb)
margprob |
Vector of marginal probabilities. |
corr |
Vector of correlation values for normal distribution. |
method |
Either "integrate" or "monte carlo" . |
n1 |
Number of normal variates if method is "monte carlo" . |
n2 |
Number of repetitions if method is "monte carlo" . |
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, http://www.wu-wien.ac.at/am
simul.commonprob(seq(0,1,0.5), seq(-1,1,0.5), meth="mo", n1=10^4)