check.commonprob {bindata} | R Documentation |
The main diagonal elements commonprob[i,i]
are interpreted as
probabilities p_{A_i}
that a binary variable A_i
equals 1. The
off-diagonal elements commonprob[i,j]
are the probabilities
p_{A_iA_j}
that both A_i
and A_j
are 1.
This programs checks some necessary conditions on these probabilities
which must be fulfilled in order that a joint distribution of the
A_i
with the given probabilities can exist.
The conditions checked are
0 \leq p_{A_i} \leq 1
\max(0, p_{A_i} + p_{A_j} - 1) \leq p_{A_iA_j} \leq
\min(p_{A_i}, p_{A_j}), i \neq j
p_{A_i} + p_{A_j} + p_{A_k} - p_{A_iA_j} -p_{A_iA_k} - p_{A_jA_k}
\leq 1, i \neq j, i \neq k, j \neq k
check.commonprob(commonprob)
commonprob |
Matrix of pairwise probabilities. |
check.commonprob
returns TRUE
, if all conditions are
fulfilled. The attribute "message"
of the return value contains
some information on the errors that were found.
Andreas Weingessel
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
,
commonprob2sigma
check.commonprob(cbind(c(0.5, 0.4), c(0.4, 0.8)))
check.commonprob(cbind(c(0.5, 0.25), c(0.25, 0.8)))
check.commonprob(cbind(c(0.5, 0, 0), c(0, 0.5, 0), c(0, 0, 0.5)))