Nothing
test_that(
"test C and R engine DyNAM-rate",
{
skip_on_cran()
model <- "DyNAM"
subModel <- "rate"
# endogenous and right-censored events
formula <- depNetwork ~ 1 + indeg + outdeg(networkExog, weighted = TRUE)
modR <- estimate(
formula,
model = model,
subModel = subModel,
estimationInit = list(
startTime = 0,
# fixedParameters = c(offsetInt, 0, 0),
returnIntervalLogL = TRUE
),
progress = FALSE,
verbose = FALSE
)
modCd <- estimate(
formula,
model = model,
subModel = subModel,
estimationInit = list(
startTime = 0, engine = "default_c",
# fixedParameters = c(offsetInt, 0, 0),
returnIntervalLogL = TRUE
)
)
modCgc <- estimate(
formula,
model = model,
subModel = subModel,
estimationInit = list(startTime = 0, engine = "gather_compute")
)
expect_equal(coef(modR), coef(modCd))
expect_equal(coef(modR), coef(modCgc))
expect_equal(vcov(modR), vcov(modCd))
expect_equal(vcov(modR), vcov(modCgc))
}
)
test_that(
"test C and R engine DyNAM-rate ordered",
{
skip_on_cran()
model <- "DyNAM"
subModel <- "rate"
# endogenous and right-censored events
formula <- depNetwork ~ indeg + outdeg(networkExog, weighted = TRUE)
modR <- estimate(
formula,
model = model,
subModel = subModel,
estimationInit = list(startTime = 0)
)
modCd <- estimate(
formula,
model = model,
subModel = subModel,
estimationInit = list(startTime = 0, engine = "default_c")
)
modCgc <- estimate(
formula,
model = model,
subModel = subModel,
estimationInit = list(startTime = 0, engine = "gather_compute")
)
expect_equal(coef(modR), coef(modCd))
expect_equal(coef(modR), coef(modCgc))
expect_equal(vcov(modR), vcov(modCd))
expect_equal(vcov(modR), vcov(modCgc))
}
)
test_that(
"test C and R engine DyNAM-choice",
{
skip_on_cran()
model <- "DyNAM"
subModel <- "choice"
# endogenous and right-censored events
formula <- depNetwork ~ inertia + indeg +
outdeg(networkExog, weighted = TRUE)
modR <- estimate(
formula,
model = model,
subModel = subModel,
estimationInit = list(startTime = 0)
)
modCd <- estimate(
formula,
model = model,
subModel = subModel,
estimationInit = list(startTime = 0, engine = "default_c")
)
modCgc <- estimate(
formula,
model = model,
subModel = subModel,
estimationInit = list(startTime = 0, engine = "gather_compute")
)
expect_equal(coef(modR), coef(modCd))
expect_equal(coef(modR), coef(modCgc))
expect_equal(vcov(modR), vcov(modCd))
expect_equal(vcov(modR), vcov(modCgc))
}
)
test_that(
"test C and R engine REM",
{
skip_on_cran()
model <- "REM"
# endogenous and right-censored events
formula <- depNetwork ~ 1 + inertia + indeg +
outdeg(networkExog, type = "ego", weighted = TRUE)
modR <- estimate(
formula,
model = model,
estimationInit = list(startTime = 0)
)
modCd <- estimate(
formula,
model = model,
estimationInit = list(startTime = 0, engine = "default_c")
)
modCgc <- estimate(
formula,
model = model,
estimationInit = list(startTime = 0, engine = "gather_compute")
)
expect_equal(coef(modR), coef(modCd))
expect_equal(coef(modR), coef(modCgc))
expect_equal(vcov(modR), vcov(modCd))
expect_equal(vcov(modR), vcov(modCgc))
}
)
test_that(
"test C and R engine REM ordered",
{
skip_on_cran()
model <- "REM"
# endogenous and right-censored events
formula <- depNetwork ~ inertia + indeg +
outdeg(networkExog, type = "ego", weighted = TRUE)
modR <- estimate(
formula,
model = model,
estimationInit = list(startTime = 0)
)
modCd <- estimate(
formula,
model = model,
estimationInit = list(startTime = 0, engine = "default_c")
)
modCgc <- estimate(
formula,
model = model,
estimationInit = list(startTime = 0, engine = "gather_compute")
)
expect_equal(coef(modR), coef(modCd))
expect_equal(coef(modR), coef(modCgc))
expect_equal(vcov(modR), vcov(modCd))
expect_equal(vcov(modR), vcov(modCgc))
}
)
test_that(
"test C and R engine DyNAM-choice_coordination",
{
skip_on_cran()
model <- "DyNAM"
subModel <- "choice_coordination"
# endogenous and right-censored events
formula <- depNetwork ~ inertia + indeg +
indeg(networkExog, type = "ego", weighted = TRUE)
modR <- estimate(
formula,
model = model,
subModel = subModel,
estimationInit = list(startTime = 0)
)
modCd <- estimate(
formula,
model = model,
subModel = subModel,
estimationInit = list(startTime = 0, engine = "default_c")
)
modCgc <- estimate(
formula,
model = model,
subModel = subModel,
estimationInit = list(startTime = 0, engine = "gather_compute")
)
expect_equal(coef(modR), coef(modCd))
expect_equal(coef(modR), coef(modCgc))
expect_equal(vcov(modR), vcov(modCd))
expect_equal(vcov(modR), vcov(modCgc))
}
)
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