Nothing
tests/testthat/test-test_covariance.R
In CovCorTest: Statistical Tests for Covariance and Correlation Matrices and their Structures
# Loading the dataset
data("EEGwide", package = "MANOVA.RM")
vars <- colnames(EEGwide)[1:6]
d <- 6
p <- d * (d + 1) / 2
X_list <- list(t(EEGwide[EEGwide$sex == "M" &
EEGwide$diagnosis == "AD", vars]),
t(EEGwide[EEGwide$sex == "M" &
EEGwide$diagnosis == "MCI", vars]),
t(EEGwide[EEGwide$sex == "M" &
EEGwide$diagnosis == "SCC", vars]),
t(EEGwide[EEGwide$sex == "W" &
EEGwide$diagnosis == "AD", vars]),
t(EEGwide[EEGwide$sex == "W" &
EEGwide$diagnosis == "MCI", vars]),
t(EEGwide[EEGwide$sex == "W" &
EEGwide$diagnosis == "SCC", vars]))
X_matrix <- matrix(unlist(X_list), nrow = 6)
X <- X_list[[1]]
nv <- c(12, 27, 20, 24, 30, 47)
## Multiple Groups
test_that("test_covariance multi groups Teststatistic", {
# Equal-Trace
expect_equal(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "equal-trace",
method = "MC",
repetitions = 1000
)$Teststatistic,
4.9047045
)
expect_equal(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "equal-trace",
method = "BT",
repetitions = 1000
)$Teststatistic,
4.9047045
)
# Equal
expect_equal(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "equal",
method = "MC",
repetitions = 1000
)$Teststatistic,
2.9384292
)
expect_equal(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "equal",
method = "BT",
repetitions = 1000
)$Teststatistic,
2.9384292
)
# Equal-Diagonals
expect_equal(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "equal-diagonals",
method = "MC",
repetitions = 1000
)$Teststatistic,
2.7304562
)
expect_equal(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "equal-diagonals",
method = "BT",
repetitions = 1000
)$Teststatistic,
2.7304562
)
})
test_that("test_covariance multi groups pvalues", {
# Equal-Trace
set.seed(31415)
expect_equal(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "equal-trace",
method = "MC",
repetitions = 1000
)$pvalue,
0.027
)
set.seed(31415)
expect_equal(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "equal-trace",
method = "BT",
repetitions = 1000
)$pvalue,
0.046
)
# Equal
set.seed(31415)
expect_equal(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "equal",
method = "MC",
repetitions = 1000
)$pvalue,
0.035
)
set.seed(31415)
expect_equal(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "equal",
method = "BT",
repetitions = 1000
)$pvalue,
0.065
)
# Equal-Diagonals
set.seed(31415)
expect_equal(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "equal-diagonals",
method = "MC",
repetitions = 1000
)$pvalue,
0.064
)
set.seed(31415)
expect_equal(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "equal-diagonals",
method = "BT",
repetitions = 1000
)$pvalue,
0.085
)
})
test_that("test_covariance multi groups wrong hypothesis", {
expect_error(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "uncorrelated",
method = "MC",
repetitions = 1000
)
)
expect_error(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "given-trace",
method = "MC",
repetitions = 1000
)
)
expect_error(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "given-matrix",
method = "MC",
repetitions = 1000
)
)
expect_error(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "equals",
method = "MC",
repetitions = 1000
)
)
})
test_that("test_covariance multi groups dimensions do not fit", {
expect_warning(expect_error(
test_covariance(
X = lapply(X_list, t),
nv = nv,
hypothesis = "equal",
method = "MC",
repetitions = 1000
)
))
expect_warning(
test_covariance(
X = X_list,
nv = nv[-1],
hypothesis = "equal",
method = "MC",
repetitions = 1000
)
)
})
test_that("test_covariance multi groups different input formats", {
expect_equal(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "equal-trace",
method = "MC",
repetitions = 1000
)$Teststatistic,
4.9047045
)
expect_warning(expect_equal(
test_covariance(
X = X_list,
nv = NULL,
hypothesis = "equal-trace",
method = "MC",
repetitions = 1000
)$Teststatistic,
4.9047045
))
expect_equal(
test_covariance(
X = X_matrix,
nv = nv,
hypothesis = "equal-trace",
method = "MC",
repetitions = 1000
)$Teststatistic,
4.9047045
)
expect_error(
test_covariance(
X = X_matrix,
nv = nv[-1],
hypothesis = "equal-trace",
method = "MC",
repetitions = 1000
)
)
})
## Single Group
test_that("test_covariance single group teststatistics", {
# Equal
expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "equal",
method = "MC",
repetitions = 1000
)$Teststatistic,
1.59396724
)
expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "equal",
method = "BT",
repetitions = 1000
)$Teststatistic,
1.59396724
)
# Given Trace
expect_warning(expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "given-trace",
method = "BT",
repetitions = 1000
)$Teststatistic,
7.1450555
))
expect_warning(expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "given-trace",
method = "MC",
repetitions = 1000
)$Teststatistic,
7.1450555
))
# Given Matrix
expect_warning(expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "given-matrix",
method = "BT",
repetitions = 1000
)$Teststatistic,
3.1849761
))
expect_warning(expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "given-matrix",
method = "MC",
repetitions = 1000
)$Teststatistic,
3.1849761
))
# Uncorrelated
expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "uncorrelated",
method = "MC",
repetitions = 1000
)$Teststatistic,
4.8878026
)
expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "uncorrelated",
method = "BT",
repetitions = 1000
)$Teststatistic,
4.8878026
)
})
test_that("test_covariance single group pvalue", {
# Equal
set.seed(31415)
expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "equal",
method = "MC",
repetitions = 1000
)$pvalue,
0.212
)
set.seed(31415)
expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "equal",
method = "BT",
repetitions = 1000
)$pvalue,
0.265
)
# Given Trace
set.seed(31415)
expect_warning(expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "given-trace",
method = "BT",
repetitions = 1000
)$pvalue,
0.028
))
set.seed(31415)
expect_warning(expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "given-trace",
method = "MC",
repetitions = 1000
)$pvalue,
0.004
))
# Given Matrix
set.seed(31415)
expect_warning(expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "given-matrix",
method = "BT",
repetitions = 1000
)$pvalue,
0.083
))
set.seed(31415)
expect_warning(expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "given-matrix",
method = "MC",
repetitions = 1000
)$pvalue,
0.032
))
# Uncorrelated
set.seed(31415)
expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "uncorrelated",
method = "MC",
repetitions = 1000
)$pvalue,
0.017
)
set.seed(31415)
expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "uncorrelated",
method = "BT",
repetitions = 1000
)$pvalue,
0.047
)
})
test_that("test_covariance single group given trace/matrix", {
# Given Trace
expect_error(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "given-trace",
method = "MC",
A = c(1, 2, 3),
repetitions = 1000
)
)
expect_error(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "given-trace",
method = "MC",
A = "a",
repetitions = 1000
)
)
set.seed(31415)
expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "given-trace",
method = "MC",
A = 18,
repetitions = 1000
)$pvalue,
0.981
)
# Given Matrix
expect_error(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "given-matrix",
method = "MC",
A = 1,
repetitions = 1000
)
)
expect_error(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "given-matrix",
method = "MC",
A = matrix(rnorm(10), 2, 5),
repetitions = 1000
)
)
set.seed(31415)
expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "given-matrix",
method = "MC",
A = var(t(X_list[[1]])) + seq(0, 0.7, length.out = 36),
repetitions = 1000
)$pvalue,
0.954
)
})
test_that("test_covariance single group wrong hypothesis", {
expect_error(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "equal-trace",
method = "MC",
repetitions = 1000
)
)
expect_error(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "equal-diagonals",
method = "MC",
repetitions = 1000
)
)
expect_warning(test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "equal",
A = 1
))
expect_error(test_covariance(
X = X_list,
nv = nv,
hypothesis = "uncorrelated"
))
})
test_that("test_covariance single group different input formats", {
expect_error(
test_covariance(
X = X_list[[1]],
nv = nv,
hypothesis = "equal",
method = "MC",
repetitions = 1000
)
)
expect_warning(
test_covariance(
X = X_list[[1]],
nv = 17,
hypothesis = "equal",
method = "MC",
repetitions = 1000
)
)
expect_warning(test_covariance(
X = list(X_list[[1]]),
nv = 15,
hypothesis = "equal"
))
expect_warning(test_covariance(
X = list(X_list[[1]]),
nv = nv,
hypothesis = "equal"
))
})
test_that("test_covariance wrong method", {
set.seed(31415)
expect_error(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "equal",
method = "abc",
repetitions = 1000
)
)
set.seed(31415)
expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "equal",
method = "mc",
repetitions = 1000
)$Teststatistic,
1.59396723756539
)
})
## Structure
test_that("test_covariance_structure teststatistics", {
expect_equal(
test_covariance_structure(X, structure = "autoregressive",
method = "MC")$Teststatistic,
2.14534594320388
)
expect_equal(
test_covariance_structure(X, structure = "ar", method = "BT")$Teststatistic,
2.14534594320388
)
expect_equal(
test_covariance_structure(X, structure = "FO-autoregressive",
method = "MC")$Teststatistic,
1.63857996457449
)
expect_equal(
test_covariance_structure(X, structure = "FO-ar",
method = "BT")$Teststatistic,
1.63857996457449
)
expect_equal(
test_covariance_structure(X, structure = "diagonal",
method = "MC")$Teststatistic,
4.88780263620412
)
expect_equal(
test_covariance_structure(X, structure = "diag",
method = "BT")$Teststatistic,
4.88780263620412
)
expect_equal(
test_covariance_structure(X, structure = "sphericity",
method = "MC")$Teststatistic,
3.10441188918666
)
expect_equal(
test_covariance_structure(X, structure = "spher",
method = "BT")$Teststatistic,
3.10441188918666
)
expect_equal(
test_covariance_structure(X, structure = "compoundsymmetry",
method = "MC")$Teststatistic,
1.65692260204835
)
expect_equal(
test_covariance_structure(X, structure = "cs", method = "BT")$Teststatistic,
1.65692260204835
)
expect_equal(
test_covariance_structure(X, structure = "toeplitz",
method = "MC")$Teststatistic,
1.63921322978212
)
expect_equal(
test_covariance_structure(X, structure = "toep",
method = "BT")$Teststatistic,
1.63921322978212
)
})
test_that("test_covariance_structure pvalue", {
set.seed(31415)
expect_equal(
test_covariance_structure(
X,
structure = "autoregressive",
method = "MC",
)$pvalue,
0.129
)
set.seed(31415)
expect_equal(
test_covariance_structure(
X,
structure = "ar",
method = "BT",
)$pvalue,
0.142
)
set.seed(31415)
expect_equal(
test_covariance_structure(
X,
structure = "FO-autoregressive",
method = "MC",
)$pvalue,
0.197
)
set.seed(31415)
expect_equal(
test_covariance_structure(
X,
structure = "FO-ar",
method = "BT",
)$pvalue,
0.214
)
set.seed(31415)
expect_equal(
test_covariance_structure(
X,
structure = "diagonal",
method = "MC",
)$pvalue,
0.017
)
set.seed(31415)
expect_equal(
test_covariance_structure(
X,
structure = "diag",
method = "BT",
)$pvalue,
0.053
)
set.seed(31415)
expect_equal(
test_covariance_structure(
X,
structure = "sphericity",
method = "MC",
)$pvalue,
0.033
)
set.seed(31415)
expect_equal(
test_covariance_structure(
X,
structure = "spher",
method = "BT",
)$pvalue,
0.077
)
set.seed(31415)
expect_equal(
test_covariance_structure(
X,
structure = "compoundsymmetry",
method = "MC",
)$pvalue,
0.177
)
set.seed(31415)
expect_equal(
test_covariance_structure(
X,
structure = "cs",
method = "BT",
)$pvalue,
0.227
)
set.seed(31415)
expect_equal(
test_covariance_structure(
X,
structure = "toeplitz",
method = "MC",
)$pvalue,
0.18
)
set.seed(31415)
expect_equal(
test_covariance_structure(
X,
structure = "toep",
method = "BT",
)$pvalue,
0.232
)
})
test_that("test_covariance_structure wrong method", {
set.seed(31415)
expect_error(
test_covariance_structure(
X = X,
structure = "cs",
method = "abc",
repetitions = 1000
)
)
set.seed(31415)
expect_equal(
test_covariance_structure(
X = X,
structure = "cs",
method = "mc",
repetitions = 1000
)$Teststatistic,
1.65692260204835
)
})
test_that("test_covariance_structure input list", {
set.seed(31415)
expect_warning(expect_equal(
test_covariance_structure(
X = X_list,
structure = "cs",
method = "mc",
repetitions = 1000
)$pvalue,
0.177
))
set.seed(31415)
expect_equal(
test_covariance_structure(
X = list(X),
structure = "cs",
method = "mc",
repetitions = 1000
)$pvalue,
0.177
)
})
test_that("test_covariance_structure wrong dimension / hypothesis", {
expect_error(test_covariance_structure(
X = X_list[[1]][1, 1:12, drop = FALSE],
structure = "cs",
method = "BT"
))
expect_error(test_covariance_structure(
X = X_list[[1]],
structure = "a",
method = "BT"
))
})
## Base
C <- matrix(c(1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 1),
nrow = 1,
ncol = 21)
Xi <- 2
test_that("test_covariance no hypothesis, C or Xi missing", {
expect_error(test_covariance(
X = X_list, nv = nv, C = C
))
})
test_that("test_covariance pvalue,statistic", {
set.seed(31415)
expect_equal(
test_covariance(
X = X,
nv = NULL,
C = C,
Xi = Xi,
method = "BT",
repetitions = 1000
)$pvalue,
0.038
)
set.seed(31415)
expect_equal(
test_covariance(
X = X,
nv = NULL,
C = C,
Xi = Xi,
method = "BT",
repetitions = 1000
)$Teststatistic,
6.32190311190589
)
set.seed(31415)
expect_equal(
test_covariance(
X = X,
nv = NULL,
C = C,
Xi = Xi,
method = "BT",
repetitions = 1000
,
hypothesis = NULL
)$pvalue,
0.038
)
})
test_that("test_covariance dimensions", {
C <- matrix(c(1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 1),
nrow = 1,
ncol = 21)
Xi <- 2
set.seed(31415)
expect_error(
test_covariance(
X = X,
nv = NULL,
C = C[1, 1:20],
Xi = Xi,
method = "BT",
repetitions = 1000
)
)
set.seed(31415)
expect_error(
test_covariance(
X = X,
nv = NULL,
C = C[1, 1:20, drop = FALSE],
Xi = Xi,
method = "BT",
repetitions = 1000
)
)
})
test_that("test_covariance wrong method", {
C <- matrix(c(1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 1),
nrow = 1,
ncol = 21)
Xi <- 2
set.seed(31415)
expect_error(
test_covariance(
X = X,
nv = NULL,
C = C[1, 1:20],
Xi = Xi,
method = "abc",
repetitions = 1000
)
)
})
## Printing
test_that("print covtest", {
X <- CovTest()
expect_null(print(X))
})
## Missing values
test_that("missing values one group", {
matrix <- matrix(
c(1, NA, 3, NA, NA, NA, 2, 4, NA, NA, 6, 7, 1, 2, 3, 4, 5, 6),
nrow = 3,
byrow = TRUE
)
expect_error(expect_warning(
test_covariance(
X = matrix,
nv = NULL,
hypothesis = "uncorrelated"
)
))
matrix <- matrix(c(NA, NA, NA, NA, 1, NA, 2, 4, 4, NA, 6, 7),
nrow = 3,
byrow = TRUE)
expect_warning(expect_warning(
test_covariance(
X = matrix,
nv = NULL,
hypothesis = "uncorrelated"
)
))
})
test_that("missing values mutliple groups", {
X <- list(
matrix1 = matrix(
c(1, NA, 3, NA, 2, NA, 2, 4, 1, NA, 6, 7, 1, 2, 3, 4, 5, 6, 7, 8, 9),
nrow = 3,
byrow = TRUE
),
matrix2 = matrix(
c(5, NA, 1, NA, 9, NA, 4, NA, 3, 5, 8, NA),
nrow = 3,
byrow = TRUE
),
matrix3 = matrix(
c(2, NA, 2, NA, 4, NA, 2, 4, 1, NA, 6, 7),
nrow = 3,
byrow = TRUE
),
matrix4 = matrix(
c(7, NA, 6, NA, 7, NA, 4, NA, 3, 5, 8, NA),
nrow = 3,
byrow = TRUE
)
)
expect_warning(test_covariance(
X = X,
nv = c(7, 4, 4, 4),
hypothesis = "equal"
))
X <- list(
matrix1 = matrix(
c(1, NA, 3, NA, 2, NA, 2, 4, 1, NA, 6, 7, 1, 2, 3, 4, 5, 6, 7, 8, 9),
nrow = 3,
byrow = TRUE
),
matrix2 = matrix(
c(NA, NA, NA, NA, 9, NA, 4, NA, 3, 5, 8, NA),
nrow = 3,
byrow = TRUE
),
matrix3 = matrix(
c(2, NA, 2, NA, 4, NA, 2, 4, 1, NA, 6, 7),
nrow = 3,
byrow = TRUE
),
matrix4 = matrix(
c(7, NA, 6, NA, 7, NA, 4, NA, 3, 5, 8, NA),
nrow = 3,
byrow = TRUE
)
)
expect_warning(expect_warning(
test_covariance(
X = X,
nv = c(7, 4, 4, 4),
hypothesis = "equal"
)
))
})
## wrong dimensions: only one subject, only one variable
test_that("dim = 1 one group", {
X <- matrix(c(1, 2, 3, 4, 5, 6), nrow = 1)
expect_error(test_covariance(X, hypothesis = "equal"))
X <- matrix(c(1, 2, 3, 4, 5, 6), ncol = 1)
expect_error(test_covariance(X, hypothesis = "equal"))
})
test_that("dim = 1 multiple groups", {
X <- list(matrix(c(1, 2, 3, 4, 5, 6), nrow = 3), matrix(c(1, 2, 3), nrow = 3))
expect_error(test_covariance(X, nv = c(2, 1), hypothesis = "equal"))
X <- list(matrix(c(1, 2, 3, 4, 5, 6), nrow = 1), matrix(c(1, 2, 3), nrow = 1))
expect_error(test_covariance(X, nv = c(6, 3), hypothesis = "equal"))
})
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# Loading the dataset
data("EEGwide", package = "MANOVA.RM")
vars <- colnames(EEGwide)[1:6]
d <- 6
p <- d * (d + 1) / 2
X_list <- list(t(EEGwide[EEGwide$sex == "M" &
EEGwide$diagnosis == "AD", vars]),
t(EEGwide[EEGwide$sex == "M" &
EEGwide$diagnosis == "MCI", vars]),
t(EEGwide[EEGwide$sex == "M" &
EEGwide$diagnosis == "SCC", vars]),
t(EEGwide[EEGwide$sex == "W" &
EEGwide$diagnosis == "AD", vars]),
t(EEGwide[EEGwide$sex == "W" &
EEGwide$diagnosis == "MCI", vars]),
t(EEGwide[EEGwide$sex == "W" &
EEGwide$diagnosis == "SCC", vars]))
X_matrix <- matrix(unlist(X_list), nrow = 6)
X <- X_list[[1]]
nv <- c(12, 27, 20, 24, 30, 47)
## Multiple Groups
test_that("test_covariance multi groups Teststatistic", {
# Equal-Trace
expect_equal(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "equal-trace",
method = "MC",
repetitions = 1000
)$Teststatistic,
4.9047045
)
expect_equal(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "equal-trace",
method = "BT",
repetitions = 1000
)$Teststatistic,
4.9047045
)
# Equal
expect_equal(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "equal",
method = "MC",
repetitions = 1000
)$Teststatistic,
2.9384292
)
expect_equal(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "equal",
method = "BT",
repetitions = 1000
)$Teststatistic,
2.9384292
)
# Equal-Diagonals
expect_equal(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "equal-diagonals",
method = "MC",
repetitions = 1000
)$Teststatistic,
2.7304562
)
expect_equal(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "equal-diagonals",
method = "BT",
repetitions = 1000
)$Teststatistic,
2.7304562
)
})
test_that("test_covariance multi groups pvalues", {
# Equal-Trace
set.seed(31415)
expect_equal(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "equal-trace",
method = "MC",
repetitions = 1000
)$pvalue,
0.027
)
set.seed(31415)
expect_equal(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "equal-trace",
method = "BT",
repetitions = 1000
)$pvalue,
0.046
)
# Equal
set.seed(31415)
expect_equal(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "equal",
method = "MC",
repetitions = 1000
)$pvalue,
0.035
)
set.seed(31415)
expect_equal(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "equal",
method = "BT",
repetitions = 1000
)$pvalue,
0.065
)
# Equal-Diagonals
set.seed(31415)
expect_equal(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "equal-diagonals",
method = "MC",
repetitions = 1000
)$pvalue,
0.064
)
set.seed(31415)
expect_equal(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "equal-diagonals",
method = "BT",
repetitions = 1000
)$pvalue,
0.085
)
})
test_that("test_covariance multi groups wrong hypothesis", {
expect_error(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "uncorrelated",
method = "MC",
repetitions = 1000
)
)
expect_error(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "given-trace",
method = "MC",
repetitions = 1000
)
)
expect_error(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "given-matrix",
method = "MC",
repetitions = 1000
)
)
expect_error(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "equals",
method = "MC",
repetitions = 1000
)
)
})
test_that("test_covariance multi groups dimensions do not fit", {
expect_warning(expect_error(
test_covariance(
X = lapply(X_list, t),
nv = nv,
hypothesis = "equal",
method = "MC",
repetitions = 1000
)
))
expect_warning(
test_covariance(
X = X_list,
nv = nv[-1],
hypothesis = "equal",
method = "MC",
repetitions = 1000
)
)
})
test_that("test_covariance multi groups different input formats", {
expect_equal(
test_covariance(
X = X_list,
nv = nv,
hypothesis = "equal-trace",
method = "MC",
repetitions = 1000
)$Teststatistic,
4.9047045
)
expect_warning(expect_equal(
test_covariance(
X = X_list,
nv = NULL,
hypothesis = "equal-trace",
method = "MC",
repetitions = 1000
)$Teststatistic,
4.9047045
))
expect_equal(
test_covariance(
X = X_matrix,
nv = nv,
hypothesis = "equal-trace",
method = "MC",
repetitions = 1000
)$Teststatistic,
4.9047045
)
expect_error(
test_covariance(
X = X_matrix,
nv = nv[-1],
hypothesis = "equal-trace",
method = "MC",
repetitions = 1000
)
)
})
## Single Group
test_that("test_covariance single group teststatistics", {
# Equal
expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "equal",
method = "MC",
repetitions = 1000
)$Teststatistic,
1.59396724
)
expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "equal",
method = "BT",
repetitions = 1000
)$Teststatistic,
1.59396724
)
# Given Trace
expect_warning(expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "given-trace",
method = "BT",
repetitions = 1000
)$Teststatistic,
7.1450555
))
expect_warning(expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "given-trace",
method = "MC",
repetitions = 1000
)$Teststatistic,
7.1450555
))
# Given Matrix
expect_warning(expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "given-matrix",
method = "BT",
repetitions = 1000
)$Teststatistic,
3.1849761
))
expect_warning(expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "given-matrix",
method = "MC",
repetitions = 1000
)$Teststatistic,
3.1849761
))
# Uncorrelated
expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "uncorrelated",
method = "MC",
repetitions = 1000
)$Teststatistic,
4.8878026
)
expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "uncorrelated",
method = "BT",
repetitions = 1000
)$Teststatistic,
4.8878026
)
})
test_that("test_covariance single group pvalue", {
# Equal
set.seed(31415)
expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "equal",
method = "MC",
repetitions = 1000
)$pvalue,
0.212
)
set.seed(31415)
expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "equal",
method = "BT",
repetitions = 1000
)$pvalue,
0.265
)
# Given Trace
set.seed(31415)
expect_warning(expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "given-trace",
method = "BT",
repetitions = 1000
)$pvalue,
0.028
))
set.seed(31415)
expect_warning(expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "given-trace",
method = "MC",
repetitions = 1000
)$pvalue,
0.004
))
# Given Matrix
set.seed(31415)
expect_warning(expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "given-matrix",
method = "BT",
repetitions = 1000
)$pvalue,
0.083
))
set.seed(31415)
expect_warning(expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "given-matrix",
method = "MC",
repetitions = 1000
)$pvalue,
0.032
))
# Uncorrelated
set.seed(31415)
expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "uncorrelated",
method = "MC",
repetitions = 1000
)$pvalue,
0.017
)
set.seed(31415)
expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "uncorrelated",
method = "BT",
repetitions = 1000
)$pvalue,
0.047
)
})
test_that("test_covariance single group given trace/matrix", {
# Given Trace
expect_error(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "given-trace",
method = "MC",
A = c(1, 2, 3),
repetitions = 1000
)
)
expect_error(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "given-trace",
method = "MC",
A = "a",
repetitions = 1000
)
)
set.seed(31415)
expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "given-trace",
method = "MC",
A = 18,
repetitions = 1000
)$pvalue,
0.981
)
# Given Matrix
expect_error(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "given-matrix",
method = "MC",
A = 1,
repetitions = 1000
)
)
expect_error(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "given-matrix",
method = "MC",
A = matrix(rnorm(10), 2, 5),
repetitions = 1000
)
)
set.seed(31415)
expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "given-matrix",
method = "MC",
A = var(t(X_list[[1]])) + seq(0, 0.7, length.out = 36),
repetitions = 1000
)$pvalue,
0.954
)
})
test_that("test_covariance single group wrong hypothesis", {
expect_error(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "equal-trace",
method = "MC",
repetitions = 1000
)
)
expect_error(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "equal-diagonals",
method = "MC",
repetitions = 1000
)
)
expect_warning(test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "equal",
A = 1
))
expect_error(test_covariance(
X = X_list,
nv = nv,
hypothesis = "uncorrelated"
))
})
test_that("test_covariance single group different input formats", {
expect_error(
test_covariance(
X = X_list[[1]],
nv = nv,
hypothesis = "equal",
method = "MC",
repetitions = 1000
)
)
expect_warning(
test_covariance(
X = X_list[[1]],
nv = 17,
hypothesis = "equal",
method = "MC",
repetitions = 1000
)
)
expect_warning(test_covariance(
X = list(X_list[[1]]),
nv = 15,
hypothesis = "equal"
))
expect_warning(test_covariance(
X = list(X_list[[1]]),
nv = nv,
hypothesis = "equal"
))
})
test_that("test_covariance wrong method", {
set.seed(31415)
expect_error(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "equal",
method = "abc",
repetitions = 1000
)
)
set.seed(31415)
expect_equal(
test_covariance(
X = X_list[[1]],
nv = NULL,
hypothesis = "equal",
method = "mc",
repetitions = 1000
)$Teststatistic,
1.59396723756539
)
})
## Structure
test_that("test_covariance_structure teststatistics", {
expect_equal(
test_covariance_structure(X, structure = "autoregressive",
method = "MC")$Teststatistic,
2.14534594320388
)
expect_equal(
test_covariance_structure(X, structure = "ar", method = "BT")$Teststatistic,
2.14534594320388
)
expect_equal(
test_covariance_structure(X, structure = "FO-autoregressive",
method = "MC")$Teststatistic,
1.63857996457449
)
expect_equal(
test_covariance_structure(X, structure = "FO-ar",
method = "BT")$Teststatistic,
1.63857996457449
)
expect_equal(
test_covariance_structure(X, structure = "diagonal",
method = "MC")$Teststatistic,
4.88780263620412
)
expect_equal(
test_covariance_structure(X, structure = "diag",
method = "BT")$Teststatistic,
4.88780263620412
)
expect_equal(
test_covariance_structure(X, structure = "sphericity",
method = "MC")$Teststatistic,
3.10441188918666
)
expect_equal(
test_covariance_structure(X, structure = "spher",
method = "BT")$Teststatistic,
3.10441188918666
)
expect_equal(
test_covariance_structure(X, structure = "compoundsymmetry",
method = "MC")$Teststatistic,
1.65692260204835
)
expect_equal(
test_covariance_structure(X, structure = "cs", method = "BT")$Teststatistic,
1.65692260204835
)
expect_equal(
test_covariance_structure(X, structure = "toeplitz",
method = "MC")$Teststatistic,
1.63921322978212
)
expect_equal(
test_covariance_structure(X, structure = "toep",
method = "BT")$Teststatistic,
1.63921322978212
)
})
test_that("test_covariance_structure pvalue", {
set.seed(31415)
expect_equal(
test_covariance_structure(
X,
structure = "autoregressive",
method = "MC",
)$pvalue,
0.129
)
set.seed(31415)
expect_equal(
test_covariance_structure(
X,
structure = "ar",
method = "BT",
)$pvalue,
0.142
)
set.seed(31415)
expect_equal(
test_covariance_structure(
X,
structure = "FO-autoregressive",
method = "MC",
)$pvalue,
0.197
)
set.seed(31415)
expect_equal(
test_covariance_structure(
X,
structure = "FO-ar",
method = "BT",
)$pvalue,
0.214
)
set.seed(31415)
expect_equal(
test_covariance_structure(
X,
structure = "diagonal",
method = "MC",
)$pvalue,
0.017
)
set.seed(31415)
expect_equal(
test_covariance_structure(
X,
structure = "diag",
method = "BT",
)$pvalue,
0.053
)
set.seed(31415)
expect_equal(
test_covariance_structure(
X,
structure = "sphericity",
method = "MC",
)$pvalue,
0.033
)
set.seed(31415)
expect_equal(
test_covariance_structure(
X,
structure = "spher",
method = "BT",
)$pvalue,
0.077
)
set.seed(31415)
expect_equal(
test_covariance_structure(
X,
structure = "compoundsymmetry",
method = "MC",
)$pvalue,
0.177
)
set.seed(31415)
expect_equal(
test_covariance_structure(
X,
structure = "cs",
method = "BT",
)$pvalue,
0.227
)
set.seed(31415)
expect_equal(
test_covariance_structure(
X,
structure = "toeplitz",
method = "MC",
)$pvalue,
0.18
)
set.seed(31415)
expect_equal(
test_covariance_structure(
X,
structure = "toep",
method = "BT",
)$pvalue,
0.232
)
})
test_that("test_covariance_structure wrong method", {
set.seed(31415)
expect_error(
test_covariance_structure(
X = X,
structure = "cs",
method = "abc",
repetitions = 1000
)
)
set.seed(31415)
expect_equal(
test_covariance_structure(
X = X,
structure = "cs",
method = "mc",
repetitions = 1000
)$Teststatistic,
1.65692260204835
)
})
test_that("test_covariance_structure input list", {
set.seed(31415)
expect_warning(expect_equal(
test_covariance_structure(
X = X_list,
structure = "cs",
method = "mc",
repetitions = 1000
)$pvalue,
0.177
))
set.seed(31415)
expect_equal(
test_covariance_structure(
X = list(X),
structure = "cs",
method = "mc",
repetitions = 1000
)$pvalue,
0.177
)
})
test_that("test_covariance_structure wrong dimension / hypothesis", {
expect_error(test_covariance_structure(
X = X_list[[1]][1, 1:12, drop = FALSE],
structure = "cs",
method = "BT"
))
expect_error(test_covariance_structure(
X = X_list[[1]],
structure = "a",
method = "BT"
))
})
## Base
C <- matrix(c(1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 1),
nrow = 1,
ncol = 21)
Xi <- 2
test_that("test_covariance no hypothesis, C or Xi missing", {
expect_error(test_covariance(
X = X_list, nv = nv, C = C
))
})
test_that("test_covariance pvalue,statistic", {
set.seed(31415)
expect_equal(
test_covariance(
X = X,
nv = NULL,
C = C,
Xi = Xi,
method = "BT",
repetitions = 1000
)$pvalue,
0.038
)
set.seed(31415)
expect_equal(
test_covariance(
X = X,
nv = NULL,
C = C,
Xi = Xi,
method = "BT",
repetitions = 1000
)$Teststatistic,
6.32190311190589
)
set.seed(31415)
expect_equal(
test_covariance(
X = X,
nv = NULL,
C = C,
Xi = Xi,
method = "BT",
repetitions = 1000
,
hypothesis = NULL
)$pvalue,
0.038
)
})
test_that("test_covariance dimensions", {
C <- matrix(c(1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 1),
nrow = 1,
ncol = 21)
Xi <- 2
set.seed(31415)
expect_error(
test_covariance(
X = X,
nv = NULL,
C = C[1, 1:20],
Xi = Xi,
method = "BT",
repetitions = 1000
)
)
set.seed(31415)
expect_error(
test_covariance(
X = X,
nv = NULL,
C = C[1, 1:20, drop = FALSE],
Xi = Xi,
method = "BT",
repetitions = 1000
)
)
})
test_that("test_covariance wrong method", {
C <- matrix(c(1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 1),
nrow = 1,
ncol = 21)
Xi <- 2
set.seed(31415)
expect_error(
test_covariance(
X = X,
nv = NULL,
C = C[1, 1:20],
Xi = Xi,
method = "abc",
repetitions = 1000
)
)
})
## Printing
test_that("print covtest", {
X <- CovTest()
expect_null(print(X))
})
## Missing values
test_that("missing values one group", {
matrix <- matrix(
c(1, NA, 3, NA, NA, NA, 2, 4, NA, NA, 6, 7, 1, 2, 3, 4, 5, 6),
nrow = 3,
byrow = TRUE
)
expect_error(expect_warning(
test_covariance(
X = matrix,
nv = NULL,
hypothesis = "uncorrelated"
)
))
matrix <- matrix(c(NA, NA, NA, NA, 1, NA, 2, 4, 4, NA, 6, 7),
nrow = 3,
byrow = TRUE)
expect_warning(expect_warning(
test_covariance(
X = matrix,
nv = NULL,
hypothesis = "uncorrelated"
)
))
})
test_that("missing values mutliple groups", {
X <- list(
matrix1 = matrix(
c(1, NA, 3, NA, 2, NA, 2, 4, 1, NA, 6, 7, 1, 2, 3, 4, 5, 6, 7, 8, 9),
nrow = 3,
byrow = TRUE
),
matrix2 = matrix(
c(5, NA, 1, NA, 9, NA, 4, NA, 3, 5, 8, NA),
nrow = 3,
byrow = TRUE
),
matrix3 = matrix(
c(2, NA, 2, NA, 4, NA, 2, 4, 1, NA, 6, 7),
nrow = 3,
byrow = TRUE
),
matrix4 = matrix(
c(7, NA, 6, NA, 7, NA, 4, NA, 3, 5, 8, NA),
nrow = 3,
byrow = TRUE
)
)
expect_warning(test_covariance(
X = X,
nv = c(7, 4, 4, 4),
hypothesis = "equal"
))
X <- list(
matrix1 = matrix(
c(1, NA, 3, NA, 2, NA, 2, 4, 1, NA, 6, 7, 1, 2, 3, 4, 5, 6, 7, 8, 9),
nrow = 3,
byrow = TRUE
),
matrix2 = matrix(
c(NA, NA, NA, NA, 9, NA, 4, NA, 3, 5, 8, NA),
nrow = 3,
byrow = TRUE
),
matrix3 = matrix(
c(2, NA, 2, NA, 4, NA, 2, 4, 1, NA, 6, 7),
nrow = 3,
byrow = TRUE
),
matrix4 = matrix(
c(7, NA, 6, NA, 7, NA, 4, NA, 3, 5, 8, NA),
nrow = 3,
byrow = TRUE
)
)
expect_warning(expect_warning(
test_covariance(
X = X,
nv = c(7, 4, 4, 4),
hypothesis = "equal"
)
))
})
## wrong dimensions: only one subject, only one variable
test_that("dim = 1 one group", {
X <- matrix(c(1, 2, 3, 4, 5, 6), nrow = 1)
expect_error(test_covariance(X, hypothesis = "equal"))
X <- matrix(c(1, 2, 3, 4, 5, 6), ncol = 1)
expect_error(test_covariance(X, hypothesis = "equal"))
})
test_that("dim = 1 multiple groups", {
X <- list(matrix(c(1, 2, 3, 4, 5, 6), nrow = 3), matrix(c(1, 2, 3), nrow = 3))
expect_error(test_covariance(X, nv = c(2, 1), hypothesis = "equal"))
X <- list(matrix(c(1, 2, 3, 4, 5, 6), nrow = 1), matrix(c(1, 2, 3), nrow = 1))
expect_error(test_covariance(X, nv = c(6, 3), hypothesis = "equal"))
})
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