Dyads() constraint now ignores preexisting %ergmlhs% constraints and observational constraints when calling ergmMPLE(). This prevents accidental infinite recursion, at the cost of speed in some circumstances.

Author: krivit

DESCRIPTION

@@ -1,5 +1,5 @@
 Package: ergm
-Version: 4.13.0-8132
+Version: 4.13.0-8133
 Date: 2026-04-08
 Title: Fit, Simulate and Diagnose Exponential-Family Models for Networks
 Authors@R: c(

R/InitErgmConstraint.operator.R

@@ -55,6 +55,7 @@ InitErgmConstraint.Dyads<-function(nw, arglist, ..., verify_dind = TRUE){
       fd <- lapply(list(fix=fix,vary=vary),
                    function(f){
                      if(!is.null(f)){
+                       nw %ergmlhs% "constraints" <- nw %ergmlhs% "obs.constraints" <- NULL
                        m <- ergmMPLE(f, basis = nw, expand.bipartite=TRUE, output="array")$predictor
                        m <- (m != 0) %|% FALSE
                        if(!is.directed(nw)){

tests/testthat/test-constrain-dind.R

@@ -124,3 +124,12 @@ test_that("Dyads() operator for bipartite undirected networks", {
   w <- outer(wealth01[1:7],wealth01[8:16],FUN=`==`)
   expect_equal(fix_g,logit(sum((!w)*m)/sum(!w)),ignore_attr=TRUE)
 })
+
+
+test_that("Dyad-independent constraint with missing edges", {
+  data(sampson)
+  samplike[1, 2] <- NA
+  truth <- coef(ergm(samplike ~ nodematch("group3")))
+  samplike %ergmlhs% "constraints" <- ~Dyads(vary = ~nodematch("group3"))
+  expect_equal(coef(ergm(samplike ~ edges)), truth, ignore_attr = TRUE)
+})