Nothing
context("tolerance_limit")
# Test that the function returns a tolerance_delta class
test_that("tolerance_limit returns a tolerance_delta class", {
# generic
expect_s3_class(tolerance_limit(data = mtcars, x = "mpg", y = "disp"), "tolerance_delta")
# all iterations
data(temps)
temps2 = temps
temps2$x = temps$trec_pre
temps2$y = temps$teso_pre
temps2$condition = temps$tod
temps2$ts = as.numeric(temps$trial_num)
expect_s3_class(tolerance_limit(data = temps2,
x = "x",
y = "y"),
"tolerance_delta")
expect_s3_class(tolerance_limit(data = temps2,
x = "x",
y = "y",
tol_method = "perc",
replicates = 20),
"tolerance_delta")
expect_s3_class(tolerance_limit(data = temps2,
x = "x",
y = "y",
keep_model = FALSE),
"tolerance_delta")
expect_s3_class(tolerance_limit(data = temps2,
x = "x",
y = "y",
id = "id"),
"tolerance_delta")
expect_s3_class(tolerance_limit(data = temps2,
x = "x",
y = "y",
id = "id",
cor_type = "ar1"),
"tolerance_delta")
expect_s3_class(tolerance_limit(data = temps2,
x = "x",
y = "y",
id = "id",
cor_type = "car1"),
"tolerance_delta")
expect_s3_class(tolerance_limit(data = temps2,
x = "x",
y = "y",
id = "id",
time = "ts",
cor_type = "ar1"),
"tolerance_delta")
expect_s3_class(tolerance_limit(data = temps2,
x = "x",
y = "y",
id = "id",
time = "ts",
cor_type = "car1"),
"tolerance_delta")
expect_s3_class(tolerance_limit(data = temps2,
x = "x",
y = "y",
id = "id",
condition = "condition",
correlation = nlme::corAR1(form=~1|id),
weights = nlme::varIdent(form=~condition)),
"tolerance_delta")
expect_s3_class(tolerance_limit(data = temps2,
x = "x",
y = "y",
id = "id",
condition = "condition",
tol_method = "p",
replicates = 20),
"tolerance_delta")
expect_s3_class(tolerance_limit(data = temps2,
x = "x",
y = "y",
id = "id",
log_tf = TRUE,
prop_bias = TRUE),
"tolerance_delta")
})
test_that("check methods",{
# all iterations
data(temps)
temps2 = temps
temps2$x = temps$trec_pre
temps2$y = temps$teso_pre
temps2$condition = temps$tod
temps2$ts = as.numeric(temps$trial_num)
test1 = tolerance_limit(data = temps2,
x = "x",
y = "y")
print(test1)
check(test1)
plot(test1,
delta = 2)
plot(test1, geom = "geom_bin2d")
plot(test1, geom = "geom_density_2d")
plot(test1, geom = "geom_density_2d_filled")
plot(test1, geom = "stat_density_2d")
expect_error(plot(test1, geom = "geom_bar"))
test1p = tolerance_limit(data = temps2,
x = "x",
y = "y",
prop_bias =TRUE)
print(test1p)
check(test1p)
plot(test1p,
delta = 2)
plot(test1p,
delta = c(-1,2))
plot(test1p, geom = "geom_bin2d")
plot(test1p, geom = "geom_density_2d")
plot(test1p, geom = "geom_density_2d_filled")
plot(test1p, geom = "stat_density_2d")
test2 = tolerance_limit(data = temps2,
x = "x",
y = "y",
id = "id")
print(test2)
check(test2)
plot(test2)
test3 = tolerance_limit(data = temps2,
x = "x",
y = "y",
id = "id",
cor_type = "ar1")
print(test3)
check(test3)
plot(test3)
test4 = tolerance_limit(data = temps2,
x = "x",
y = "y",
id = "id",
cor_type = "car1")
print(test4)
check(test4)
plot(test4)
test5 = tolerance_limit(data = temps2,
x = "x",
y = "y",
id = "id",
condition = "condition",
correlation = nlme::corAR1(form=~1|id),
weights = nlme::varIdent(form=~condition))
print(test5)
check(test5)
plot(test5)
test6 = tolerance_limit(data = temps2,
x = "x",
y = "y",
id = "id",
condition = "condition",
tol_method = "p",
replicates = 20)
print(test6)
check(test6)
plot(test6)
test7 = tolerance_limit(data = temps2,
x = "x",
y = "y",
id = "id",
log_tf = TRUE,
prop_bias = TRUE)
testthat::expect_identical(class(test7), "tolerance_delta")
print(test7)
check(test7)
plot(test7)
test8 = tolerance_limit(data = temps2,
x = "x",
y = "y",
id = "id",
condition = "condition",
log_tf = TRUE,
prop_bias = TRUE)
testthat::expect_identical(class(test8), "tolerance_delta")
print(test8)
check(test8)
plot(test8)
test9 = tolerance_limit(data = temps2,
x = "x",
y = "y",
id = "id",
condition = "condition",
log_tf = TRUE,
prop_bias = TRUE,
tol_method = "perc",
replicates = 20,
)
testthat::expect_identical(class(test8), "tolerance_delta")
print(test9)
check(test9)
plot(test9)
test10 = tolerance_limit(data = temps2,
x = "x",
y = "y",
id = "id",
# condition = "condition",
log_tf = TRUE,
prop_bias = TRUE,
tol_method = "perc",
replicates = 20,
)
testthat::expect_identical(class(test10), "tolerance_delta")
print(test10)
check(test10)
plot(test10)
x = rnorm(5500)
z = rnorm(5500,sd=.2)
y = x+z
df1 = data.frame(x,y,z)
test_big = tolerance_limit(data = df1,
x = "x",
y = "y")
check(test_big)
})
test_that("Checked against BivRegBLS", {
data(reps)
# test2 = BivRegBLS::MD.horiz.lines(data = reps, xcol = "y", ycol = "x", pred.level = .95, .95)
test1 = tolerance_limit(x = "x",
y = "y",
data = reps)
expect_equal(test1$limits$bias, .4383,
tolerance = .001)
expect_equivalent(c(test1$limits$lower.PL,
test1$limits$upper.PL),
c(-2.199752,3.076419),
tolerance = .001)
expect_equivalent(test1$limits$bias, .4383,
tolerance = .001)
} )
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