Nothing
# REQUIRE TEST Monte Carlo test ls ---------------------------------------------
test_that('REQUIRE TEST ls Monte Carlo', {
z <- zls$new()
test.ls <- z$mcunit(plot = FALSE)
expect_true(test.ls)
})
# REQUIRE TEST ls with continuous covar -----------------------------------------
test_that('REQUIRE TEST ls continuous covar -- quickstart (Zelig 5 syntax)', {
z5 <- zls$new()
z5$zelig(Fertility ~ Education, data = swiss)
# extract education coefficient parameter estimate and compare to reference
expect_equivalent(round(as.numeric(z5$get_coef()[[1]][2]), 7), -0.8623503)
})
# REQUIRE TEST ls with by -------------------------------------------------------
test_that('REQUIRE TEST ls with by', {
# Majority Catholic dummy
swiss$maj_catholic <- cut(swiss$Catholic, breaks = c(0, 51, 100))
z5by <- zls$new()
z5by$zelig(Fertility ~ Education, data = swiss, by = 'maj_catholic')
z5by$setx()
z5by$sim()
sims_df <- zelig_qi_to_df(z5by)
expect_equal(length(unique(sims_df$by)), 2)
})
# REQUIRE TEST gim method ------------------------------------------------------
#test_that('REQUIRE TESTls gim method', {
#z5$gim()
#})
# REQUIRE TEST for sim with ls models including factor levels ------------------
test_that('REQUIRE TEST for sim with models including factor levels', {
expect_is(iris$Species, 'factor')
z.out <- zelig(Petal.Width ~ Petal.Length + Species, data = iris,
model = "ls")
x.out1 <- setx(z.out, Petal.Length = 1:10)
sims1 <- sim(z.out, x.out1)
expect_equal(length(sims1$sim.out$range), 10)
x.out2 <- setx(z.out, Petal.Length = 1:10, fn = list(numeric = Median))
sims2 <- sim(z.out, x.out2)
expect_equal(length(sims2$sim.out$range), 10)
})
# REQUIRE TEST for set with ls models including factors set within zelig call ----
test_that('REQUIRE TEST for set with ls models including factors set within zelig call', {
data(macro)
z1 <- zelig(unem ~ gdp + trade + capmob + as.factor(country),
model = "ls", data = macro)
setUS1 <- setx(z1, country = "United States")
z2 <- zelig(unem ~ gdp + trade + capmob + factor(country,
labels=letters[1:14]),
model = "ls", data = macro)
setUS2 <- setx(z2, country = "m")
macro$country <- as.factor(macro$country)
z3 <- zelig(unem ~ gdp + trade + capmob + country,
model = "ls", data = macro)
setUS3 <- setx(z3, country = "United States")
expect_equal(setUS1$setx.out$x$mm[[1]][[16]], 1)
expect_equal(setUS2$setx.out$x$mm[[1]][[16]], 1)
expect_equal(setUS1$setx.out$x$mm[[1]][[16]],
setUS3$setx.out$x$mm[[1]][[16]])
expect_equal(setUS2$setx.out$x$mm[[1]][[16]],
setUS3$setx.out$x$mm[[1]][[16]])
})
# REQUIRE TEST for set with ls models including natural logs set within zelig call --
test_that('REQUIRE TEST for set with ls models including natural logs set within zelig call', {
z1 <- zelig(speed ~ log(dist), data = cars, model = 'ls')
setd1 <- setx(z1, dist = log(15))
cars$dist <- log(cars$dist)
z2 <- zelig(speed ~ dist, data = cars, model = 'ls')
setd2 <- setx(z2, dist = log(15))
expect_equal(round(setd1$setx.out$x$mm[[1]][[2]], digits = 5), 2.70805)
expect_equal(setd1$setx.out$x$mm[[1]][[2]],
setd2$setx.out$x$mm[[1]][[2]])
z3.1 <- zelig(Sepal.Length ~ log10(Petal.Length) + log(Sepal.Width),
model = 'ls', data = iris, cite = FALSE)
z3.2 <- zelig(Sepal.Length ~ log(Petal.Length, base = 10) +
log(Sepal.Width),
model = 'ls', data = iris, cite = FALSE)
expect_equal(unname(coef(z3.1)), unname(coef(z3.2)))
setz3 <- setx(z3.1)
# expect_equal(as.vector(round(unlist(setz3$setx.out$x), digits = 2)),
# c(1, 1, 1.47, 1.12))
})
# REQUIRE TEST for ls with interactions ----------------------------------------
test_that('REQUIRE TEST for ls with interactions', {
states <- as.data.frame(state.x77)
z <- zelig(Murder ~ Income * Population, data = states, model = 'ls')
s1 <- setx(z, Population = 1500:1600, Income = 3098)
s2 <- setx(z, Population = 1500:1600, Income = 6315)
expect_equal(length(s1$setx.out$range), 101)
expect_equal(length(s2$setx.out$range), 101)
})
# REQUIRE TEST for ls with unrecognised variable name --------------------------
test_that('REQUIRE TEST for ls with unrecognised variable name', {
states <- as.data.frame(state.x77)
z <- zelig(Murder ~ Income * Population, data = states, model = 'ls')
expect_error(setx(z, population = 1500:1600, Income = 3098),
"Variable 'population' not in data set.")
})
# REQUIRE TEST for ls setrange with equal length ranges ------------------------
test_that('REQUIRE TEST for ls setrange with equal length ranges and polynomials', {
iris.poly <- cbind(iris, I(iris$Petal.Length^2))
names(iris.poly)[ncol(iris.poly)] <- 'pl_2'
pl_range <- 1:7
# Polynomial found outside of formula
z.cars1 <- zelig(Sepal.Length ~ Petal.Length + pl_2 + Species,
data = iris.poly, model = 'ls', cite = FALSE)
z.cars1 <- setx(z.cars1, Species = 'virginica', Petal.Length = pl_range,
pl_2 = pl_range^2)
expect_equal(nrow(zelig_setx_to_df(z.cars1)), length(pl_range))
# Polynomial found in formula
z.cars2 <- zelig(Sepal.Length ~ Petal.Length + I(Petal.Length^2) + Species,
data = iris, model = 'ls', cite = FALSE)
z.cars2 <- setx(z.cars2, Species = 'virginica', Petal.Length = pl_range)
expect_equal(nrow(zelig_setx_to_df(z.cars2)), length(pl_range))
expect_equal(zelig_setx_to_df(z.cars1)[[2]], zelig_setx_to_df(z.cars2)[[2]])
})
# REQUIRE TEST for . formulas --------------------------------------------------
test_that('REQUIRE TEST for . formulas', {
z1 <- zelig(speed ~ ., data = cars, model = 'ls')
zset <- setx(z1, dist = 5)
expect_equal(names(coef(z1)), c("(Intercept)", "dist"))
})
# REQUIRE TEST for to_zelig within setx ----------------------------------------
test_that('REQUIRE TEST for to_zelig within setx', {
m1 <- lm(speed ~ dist, data = cars)
zset <- setx(m1, dist = 5)
expect_equal(zset$setx.out$x$mm[[1]][2], 5)
plot(sim(zset))
m2 <- glm(speed ~ dist, data = cars, family = gaussian(link = "identity"))
zset <- setx(m1, dist = 5)
expect_equal(zset$setx.out$x$mm[[1]][2], 5)
plot(sim(zset))
})
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