We discuss properties of distributions that are multivariate totally positive of order two (MTP2) related to conditional independence. In particular, we show that any independence model generated by an MTP2 distribution is a compositional semi-graphoid which is upward-stable and singleton-transitive. In addition, we prove that any MTP2 distribution satisfying an appropriate support condition is faithful to its concentration graph. Finally, we analyze factorization properties of MTP2 distributions and discuss ways of constructing MTP2 distributions; in particular, we give conditions on the log-linear parameters of a discrete distribution which ensure MTP2 and characterize conditional Gaussian distributions which satisfy MTP2
With a sequence of regressions, one may generate joint probability distributions. One starts with a ...
This note contributes to the development of the theory of stochastic dependence by employing the gen...
Conditions under which conditionally independent random variables are positive dependent are describ...
We discuss properties of distributions that are multivariate totally positive of order two (MTP$_{2}...
We discuss properties of distributions that are multivariate totally positive of order two (MTP2) re...
We discuss properties of distributions that are multivariate totally positive of order two (MTP2) re...
AbstractA function f(x) defined on X = X1 × X2 × … × Xn where each Xi is totally ordered satisfying ...
A more general definition of MTP2 (multivariate total positivity of order 2) probability measure is ...
Positive dependence is present in many real world data sets and has appealing stochastic properties ...
AbstractWe address the problem of constructing and identifying a valid joint probability density fun...
AbstractUnlike the usual stochastic order, total positivity order is closed under conditioning. Here...
© 2019 Institute of Mathematical Statistics. We analyze the problem of maximum likelihood estimation...
A concentration graph associated with a random vector is an undirected graph where each vertex corre...
Multivariate total positivity of order 2 (MTP2) is a dependence property with a number of applicatio...
AbstractA general notion of positive dependence among successive observations in a finite-state stat...
With a sequence of regressions, one may generate joint probability distributions. One starts with a ...
This note contributes to the development of the theory of stochastic dependence by employing the gen...
Conditions under which conditionally independent random variables are positive dependent are describ...
We discuss properties of distributions that are multivariate totally positive of order two (MTP$_{2}...
We discuss properties of distributions that are multivariate totally positive of order two (MTP2) re...
We discuss properties of distributions that are multivariate totally positive of order two (MTP2) re...
AbstractA function f(x) defined on X = X1 × X2 × … × Xn where each Xi is totally ordered satisfying ...
A more general definition of MTP2 (multivariate total positivity of order 2) probability measure is ...
Positive dependence is present in many real world data sets and has appealing stochastic properties ...
AbstractWe address the problem of constructing and identifying a valid joint probability density fun...
AbstractUnlike the usual stochastic order, total positivity order is closed under conditioning. Here...
© 2019 Institute of Mathematical Statistics. We analyze the problem of maximum likelihood estimation...
A concentration graph associated with a random vector is an undirected graph where each vertex corre...
Multivariate total positivity of order 2 (MTP2) is a dependence property with a number of applicatio...
AbstractA general notion of positive dependence among successive observations in a finite-state stat...
With a sequence of regressions, one may generate joint probability distributions. One starts with a ...
This note contributes to the development of the theory of stochastic dependence by employing the gen...
Conditions under which conditionally independent random variables are positive dependent are describ...