Poisson-ergmReference {ergm.count}R Documentation

Poisson-reference ERGM

Description

Specifies each dyad's baseline distribution to be Poisson with mean 1: h(y)=i,j1/yi,j!h(y)=\prod_{i,j} 1/y_{i,j}! , with the support of yi,jy_{i,j} being natural numbers (and 00 ). Using valued ERGM terms that are "generalized" from their binary counterparts, with form "sum" (see previous link for the list) produces Poisson regression. Using CMP induces a Conway-Maxwell-Poisson distribution that is Poisson when its coefficient is 00 and geometric when its coefficient is 11 .

@details Three proposal functions are currently implemented, two of them designed to improve mixing for sparse networks. They can can be selected via the ⁠MCMC.prop.weights=⁠ control parameter. The sparse proposals work by proposing a jump to 0. Both of them take an optional proposal argument p0 (i.e., MCMC.prop.args=list(p0=...) ) specifying the probability of such a jump. However, the way in which they implement it are different:

Usage

# Poisson

See Also

ergmReference for index of reference distributions currently visible to the package.

Keywords

None


[Package ergm.count version 4.1.2 Index]