Nothing
# File tests/testthat/helper-CMLE.R in package tergm, part of the
# Statnet suite of packages for network analysis, https://statnet.org .
#
# This software is distributed under the GPL-3 license. It is free,
# open source, and has the attribution requirements (GPL Section 7) at
# https://statnet.org/attribution .
#
# Copyright 2008-2023 Statnet Commons
################################################################################
logit<-function(p) log(p/(1-p))
o <- options(tergm.eval.loglik=FALSE)
CMLE.tools <- new.env()
CMLE.tools$tolerance <- 3
CMLE.tools$n <- 10
CMLE.tools$m <- 6
CMLE.tools$theta <- -1.5
CMLE.tools$z.error <- function(truth, est, variance){
if(abs(truth-est)<1e-6) 0 # Infinite case
else abs(truth-est)/sqrt(variance)
}
CMLE.tools$form.mle<-function(y0,y1,y2){
if(missing(y2)) logit(network.edgecount(y1-y0,na.omit=TRUE)/(network.dyadcount(y1)-network.edgecount(y0-is.na(y1))))
else logit((network.edgecount(y1-y0,na.omit=TRUE) +
network.edgecount(y2-y1,na.omit=TRUE))/
(network.dyadcount(y1)-network.edgecount(y0-is.na(y1)) +
network.dyadcount(y2)-network.edgecount(y1-is.na(y2))))
}
CMLE.tools$diss.mle<-function(y0,y1,y2){
if(missing(y2)) -logit(network.edgecount(y0-y1,na.omit=TRUE)/(network.edgecount(y0-is.na(y1))))
else -logit((network.edgecount(y0-y1,na.omit=TRUE) +
network.edgecount(y1-y2,na.omit=TRUE))/
(network.edgecount(y0-is.na(y1)) +
network.edgecount(y1-is.na(y2))))
}
CMLE.tools$cross.mle<-function(y0,y1,y2){
if(missing(y2)) logit(network.edgecount(y1, na.omit=TRUE)/network.dyadcount(y1, na.omit=TRUE))
else logit((network.edgecount(y1, na.omit=TRUE) +
network.edgecount(y2, na.omit=TRUE))/
(network.dyadcount(y1, na.omit=TRUE) +
network.dyadcount(y2, na.omit=TRUE)))
}
CMLE.tools$change.mle<-function(y0,y1,y2){
if(missing(y2)) logit(network.edgecount((y0-y1)|(y1-y0), na.omit=TRUE)/network.dyadcount(y1, na.omit=TRUE))
else logit((network.edgecount((y0-y1)|(y1-y0), na.omit=TRUE) +
network.edgecount((y1-y2)|(y2-y1), na.omit=TRUE))/
(network.dyadcount(y1, na.omit=TRUE) +
network.dyadcount(y2, na.omit=TRUE)))
}
CMLE.tools$do.run_2 <- function(dir, bip=FALSE, prop.weights="default"){
netdesc <- if(dir) "directed network" else {if(bip) "bipartite undirected network" else "undirected network"}
if(bip){ # Extreme theta creates networks with too few ties to properly test.
theta <- theta/2
}
y0<-network.initialize(n,dir=dir,bipartite=bip)
set.seed(321)
y0<-simulate(y0~edges, coef=theta, control=control.simulate(MCMC.burnin=n^2*2), dynamic=FALSE)
completeness <- "completely observed"
set.seed(123)
y1<-simulate(y0~edges, coef=theta, control=control.simulate(MCMC.burnin=n^2*2), dynamic=FALSE)
y2<-simulate(y1~edges, coef=theta, control=control.simulate(MCMC.burnin=n^2*2), dynamic=FALSE)
test_that(paste("Force CMPLE on", completeness, netdesc), {
set.seed(543)
fit<-tergm(list(y0,y1,y2) ~ Form(~edges) + Persist(~edges), estimate="CMPLE", times=c(1,2,3))
expect_true(fit$estimate=="CMPLE")
expect_true(z.error(form.mle(y0,y1,y2), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
expect_true(z.error(diss.mle(y0,y1,y2), coef(fit)[2], vcov(fit, sources="estimation")[2,2]) <= tolerance)
fit<-tergm(list(y0,y1,y2) ~ edges, estimate="CMPLE", times=c(1,2,3))
expect_true(fit$estimate=="CMPLE")
expect_true(z.error(cross.mle(y0,y1,y2), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
fit<-tergm(list(y0,y1,y2) ~ Cross(~edges), estimate="CMPLE", times=c(1,2,3))
expect_true(fit$estimate=="CMPLE")
expect_true(z.error(cross.mle(y0,y1,y2), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
fit<-tergm(list(y0,y1,y2) ~ Change(~edges), estimate="CMPLE", times=c(1,2,3))
expect_true(fit$estimate=="CMPLE")
expect_true(z.error(change.mle(y0,y1,y2), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
})
test_that(paste("Autodetect CMPLE on", completeness, netdesc), {
set.seed(543)
fit<-tergm(list(y0,y1,y2) ~ Form(~edges) + Persist(~edges), estimate="CMLE", times=c(1,2,3))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(form.mle(y0,y1,y2), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
expect_true(z.error(diss.mle(y0,y1,y2), coef(fit)[2], vcov(fit, sources="estimation")[2,2]) <= tolerance)
fit<-tergm(list(y0,y1,y2) ~ edges, estimate="CMLE", times=c(1,2,3))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(cross.mle(y0,y1,y2), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
fit<-tergm(list(y0,y1,y2) ~ Cross(~edges), estimate="CMLE", times=c(1,2,3))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(cross.mle(y0,y1,y2), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
fit<-tergm(list(y0,y1,y2) ~ Change(~edges), estimate="CMLE", times=c(1,2,3))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(change.mle(y0,y1,y2), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
})
for(prop.weight in prop.weights){
test_that(paste("Force CMPLE on", completeness, netdesc, "proposal", prop.weight), {
ctrl <- control.tergm(CMLE.ergm=control.ergm(force.main=TRUE, MCMC.prop.weights=prop.weight))
set.seed(543)
fit<-tergm(list(y0,y1,y2) ~ Form(~edges) + Persist(~edges), estimate="CMLE", control=ctrl, times=c(1,2,3))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(form.mle(y0,y1,y2), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
expect_true(z.error(diss.mle(y0,y1,y2), coef(fit)[2], vcov(fit, sources="estimation")[2,2]) <= tolerance)
fit<-tergm(list(y0,y1,y2) ~ edges, estimate="CMLE", control=ctrl, times=c(1,2,3))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(cross.mle(y0,y1,y2), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
fit<-tergm(list(y0,y1,y2) ~ Cross(~edges), estimate="CMLE", control=ctrl, times=c(1,2,3))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(cross.mle(y0,y1,y2), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
fit<-tergm(list(y0,y1,y2) ~ Change(~edges), estimate="CMLE", control=ctrl, times=c(1,2,3))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(change.mle(y0,y1,y2), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
})
}
completeness <- "partially observed"
y2m<-network.copy(y2)
set.seed(765)
e <- as.edgelist(y2)[1,]
y2m[e[1], e[2]] <- NA
y2m[1,m+1] <- NA
test_that(paste("Force CMPLE on", completeness, netdesc), {
set.seed(765)
fit<-tergm(list(y0,y1,y2m) ~ Form(~edges) + Persist(~edges), estimate="CMPLE", times=c(1,2,3))
expect_true(fit$estimate=="CMPLE")
expect_true(z.error(form.mle(y0,y1,y2m), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
expect_true(z.error(diss.mle(y0,y1,y2m), coef(fit)[2], vcov(fit, sources="estimation")[2,2]) <= tolerance)
fit<-tergm(list(y0,y1,y2m) ~ edges, estimate="CMPLE", times=c(1,2,3))
expect_true(fit$estimate=="CMPLE")
expect_true(z.error(cross.mle(y0,y1,y2m), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
fit<-tergm(list(y0,y1,y2m) ~ Cross(~edges), estimate="CMPLE", times=c(1,2,3))
expect_true(fit$estimate=="CMPLE")
expect_true(z.error(cross.mle(y0,y1,y2m), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
fit<-tergm(list(y0,y1,y2m) ~ Change(~edges), estimate="CMPLE", times=c(1,2,3))
expect_true(fit$estimate=="CMPLE")
expect_true(z.error(change.mle(y0,y1,y2m), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
})
test_that(paste("Autodetect CMPLE on", completeness, netdesc), {
set.seed(765)
fit<-tergm(list(y0,y1,y2m) ~ Form(~edges) + Persist(~edges), estimate="CMLE", times=c(1,2,3))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(form.mle(y0,y1,y2m), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
expect_true(z.error(diss.mle(y0,y1,y2m), coef(fit)[2], vcov(fit, sources="estimation")[2,2]) <= tolerance)
fit<-tergm(list(y0,y1,y2m) ~ edges, estimate="CMLE", times=c(1,2,3))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(cross.mle(y0,y1,y2m), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
fit<-tergm(list(y0,y1,y2m) ~ Cross(~edges), estimate="CMLE", times=c(1,2,3))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(cross.mle(y0,y1,y2m), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
fit<-tergm(list(y0,y1,y2m) ~ Change(~edges), estimate="CMLE", times=c(1,2,3))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(change.mle(y0,y1,y2m), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
})
for(prop.weight in prop.weights){
test_that(paste("Force CMPLE on", completeness, netdesc, "proposal", prop.weight), {
ctrl <- control.tergm(CMLE.ergm=control.ergm(force.main=TRUE, MCMC.prop.weights=prop.weight))
set.seed(234)
fit<-tergm(list(y0,y1,y2m) ~ Form(~edges) + Persist(~edges), estimate="CMLE", control=ctrl, times=c(1,2,3))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(form.mle(y0,y1,y2m), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
expect_true(z.error(diss.mle(y0,y1,y2m), coef(fit)[2], vcov(fit, sources="estimation")[2,2]) <= tolerance)
fit<-tergm(list(y0,y1,y2m) ~ edges, estimate="CMLE", control=ctrl, times=c(1,2,3))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(cross.mle(y0,y1,y2m), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
fit<-tergm(list(y0,y1,y2m) ~ Cross(~edges), estimate="CMLE", control=ctrl, times=c(1,2,3))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(cross.mle(y0,y1,y2m), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
fit<-tergm(list(y0,y1,y2m) ~ Change(~edges), estimate="CMLE", control=ctrl, times=c(1,2,3))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(change.mle(y0,y1,y2m), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
})
}
}
CMLE.tools$do.run_1 <- function(dir, bip=FALSE, prop.weights="default"){
netdesc <- if(dir) "directed network" else {if(bip) "bipartite undirected network" else "undirected network"}
if(bip){ # Extreme theta creates networks with too few ties to properly test.
theta <- theta/2
}
y0<-network.initialize(n,dir=dir,bipartite=bip)
set.seed(321)
y0<-simulate(y0~edges, coef=theta, control=control.simulate(MCMC.burnin=n^2*2), dynamic=FALSE)
completeness <- "completely observed"
set.seed(123)
y1<-simulate(y0~edges, coef=theta, control=control.simulate(MCMC.burnin=n^2*2), dynamic=FALSE)
test_that(paste("Force CMPLE on", completeness, netdesc), {
set.seed(543)
fit<-tergm(list(y0,y1) ~ Form(~edges) + Persist(~edges), estimate="CMPLE", times=c(1,2))
expect_true(fit$estimate=="CMPLE")
expect_true(z.error(form.mle(y0,y1), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
expect_true(z.error(diss.mle(y0,y1), coef(fit)[2], vcov(fit, sources="estimation")[2,2]) <= tolerance)
fit<-tergm(list(y0,y1) ~ edges, estimate="CMPLE", times=c(1,2))
expect_true(fit$estimate=="CMPLE")
expect_true(z.error(cross.mle(y0,y1), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
fit<-tergm(list(y0,y1) ~ Cross(~edges), estimate="CMPLE", times=c(1,2))
expect_true(fit$estimate=="CMPLE")
expect_true(z.error(cross.mle(y0,y1), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
fit<-tergm(list(y0,y1) ~ Change(~edges), estimate="CMPLE", times=c(1,2))
expect_true(fit$estimate=="CMPLE")
expect_true(z.error(change.mle(y0,y1), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
})
test_that(paste("Autodetect CMPLE on", completeness, netdesc), {
set.seed(543)
fit<-tergm(list(y0,y1) ~ Form(~edges) + Persist(~edges), estimate="CMLE", times=c(1,2))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(form.mle(y0,y1), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
expect_true(z.error(diss.mle(y0,y1), coef(fit)[2], vcov(fit, sources="estimation")[2,2]) <= tolerance)
fit<-tergm(list(y0,y1) ~ edges, estimate="CMLE", times=c(1,2))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(cross.mle(y0,y1), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
fit<-tergm(list(y0,y1) ~ Cross(~edges), estimate="CMLE", times=c(1,2))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(cross.mle(y0,y1), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
fit<-tergm(list(y0,y1) ~ Change(~edges), estimate="CMLE", times=c(1,2))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(change.mle(y0,y1), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
})
for(prop.weight in prop.weights){
test_that(paste("Force CMPLE on", completeness, netdesc, "proposal", prop.weight), {
ctrl <- control.tergm(CMLE.ergm=control.ergm(force.main=TRUE, MCMC.prop.weights=prop.weight))
set.seed(543)
fit<-tergm(list(y0,y1) ~ Form(~edges) + Persist(~edges), estimate="CMLE", control=ctrl, times=c(1,2))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(form.mle(y0,y1), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
expect_true(z.error(diss.mle(y0,y1), coef(fit)[2], vcov(fit, sources="estimation")[2,2]) <= tolerance)
fit<-tergm(list(y0,y1) ~ edges, estimate="CMLE", control=ctrl, times=c(1,2))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(cross.mle(y0,y1), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
fit<-tergm(list(y0,y1) ~ Cross(~edges), estimate="CMLE", control=ctrl, times=c(1,2))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(cross.mle(y0,y1), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
fit<-tergm(list(y0,y1) ~ Change(~edges), estimate="CMLE", control=ctrl, times=c(1,2))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(change.mle(y0,y1), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
})
}
completeness <- "partially observed"
y1m<-network.copy(y1)
set.seed(765)
e <- as.edgelist(y1)[1,]
y1m[e[1], e[2]] <- NA
y1m[1,m+1] <- NA
test_that(paste("Force CMPLE on", completeness, netdesc), {
set.seed(765)
fit<-tergm(list(y0,y1m) ~ Form(~edges) + Persist(~edges), estimate="CMPLE", times=c(1,2))
expect_true(fit$estimate=="CMPLE")
expect_true(z.error(form.mle(y0,y1m), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
expect_true(z.error(diss.mle(y0,y1m), coef(fit)[2], vcov(fit, sources="estimation")[2,2]) <= tolerance)
fit<-tergm(list(y0,y1m) ~ edges, estimate="CMPLE", times=c(1,2))
expect_true(fit$estimate=="CMPLE")
expect_true(z.error(cross.mle(y0,y1m), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
fit<-tergm(list(y0,y1m) ~ Cross(~edges), estimate="CMPLE", times=c(1,2))
expect_true(fit$estimate=="CMPLE")
expect_true(z.error(cross.mle(y0,y1m), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
fit<-tergm(list(y0,y1m) ~ Change(~edges), estimate="CMPLE", times=c(1,2))
expect_true(fit$estimate=="CMPLE")
expect_true(z.error(change.mle(y0,y1m), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
})
test_that(paste("Autodetect CMPLE on", completeness, netdesc), {
set.seed(765)
fit<-tergm(list(y0,y1m) ~ Form(~edges) + Persist(~edges), estimate="CMLE", times=c(1,2))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(form.mle(y0,y1m), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
expect_true(z.error(diss.mle(y0,y1m), coef(fit)[2], vcov(fit, sources="estimation")[2,2]) <= tolerance)
fit<-tergm(list(y0,y1m) ~ edges, estimate="CMLE", times=c(1,2))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(cross.mle(y0,y1m), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
fit<-tergm(list(y0,y1m) ~ Cross(~edges), estimate="CMLE", times=c(1,2))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(cross.mle(y0,y1m), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
fit<-tergm(list(y0,y1m) ~ Change(~edges), estimate="CMLE", times=c(1,2))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(change.mle(y0,y1m), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
})
for(prop.weight in prop.weights){
test_that(paste("Force CMPLE on", completeness, netdesc, "proposal", prop.weight), {
ctrl <- control.tergm(CMLE.ergm=control.ergm(force.main=TRUE, MCMC.prop.weights=prop.weight))
set.seed(1234)
fit<-tergm(list(y0,y1m) ~ Form(~edges) + Persist(~edges), estimate="CMLE", control=ctrl, times=c(1,2))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(form.mle(y0,y1m), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
expect_true(z.error(diss.mle(y0,y1m), coef(fit)[2], vcov(fit, sources="estimation")[2,2]) <= tolerance)
fit<-tergm(list(y0,y1m) ~ edges, estimate="CMLE", control=ctrl, times=c(1,2))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(cross.mle(y0,y1m), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
fit<-tergm(list(y0,y1m) ~ Cross(~edges), estimate="CMLE", control=ctrl, times=c(1,2))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(cross.mle(y0,y1m), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
fit<-tergm(list(y0,y1m) ~ Change(~edges), estimate="CMLE", control=ctrl, times=c(1,2))
expect_true(fit$estimate=="CMLE")
expect_true(z.error(change.mle(y0,y1m), coef(fit)[1], vcov(fit, sources="estimation")[1,1]) <= tolerance)
})
}
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.