library(simrel)
library(testthat)
context("Testing Plot Extra Functions for Multivariate Simulation.")
set.seed(2020)
sobj <- multisimrel(
n = 100,
p = 15,
q = c(5, 4, 3),
m = 5,
relpos = list(c(1, 2), c(3, 4, 6), c(5, 7)),
gamma = 0.6,
R2 = c(0.8, 0.7, 0.8),
eta = 0,
ntest = NULL,
muX = NULL,
muY = NULL,
ypos = list(c(1), c(3, 4), c(2, 5))
)
cov_xy = cov_xy(sobj)
cov_xy_sample = cov_xy(sobj, use_population=FALSE)
cov_zy = cov_zy(sobj)
cov_zy_sample = cov_zy(sobj, use_population=FALSE)
cov_zy = cov_zy(sobj)
cov_zy_sample = cov_zy(sobj, use_population=FALSE)
test_that("Tidied Beta Coefficients from simrel.", {
expect_equal(nrow(tidy_beta(sobj)), 75)
expect_equal(ncol(tidy_beta(sobj)), 3)
expect_equal(unique(tidy_beta(sobj)[['Predictor']]), 1:15)
expect_equal(unique(tidy_beta(sobj)[['Response']]), 1:5)
testthat::skip_on_cran()
expect_equal(tidy_beta(sobj)[['BetaCoef']][1], 0.08611848, tolerance = 1e-5)
})
test_that("Test Population Covariance of the simulated data.", {
expect_equal(nrow(cov_xy(sobj)), 15)
expect_equal(ncol(cov_xy(sobj)), 5)
expect_equal(cov_xy(sobj)[5, 5], 0)
testthat::skip_on_cran()
expect_equal(cov_xy(sobj)[1, 1], 0.09483724, tolerance = 1e-5)
})
test_that("Test Sample Covariance of the simulated data.", {
expect_equal(nrow(cov_xy(sobj, FALSE)), 15)
expect_equal(ncol(cov_xy(sobj, FALSE)), 5)
testthat::skip_on_cran()
expect_equal(cov_xy(sobj, FALSE)[1, 1], 0.1800116, tolerance = 1e-5)
expect_equal(cov_xy(sobj, FALSE)[5, 5], -0.01037432, tolerance = 1e-5)
})
test_that("Test tidy lambda population.", {
expect_equal(tidy_lambda(sobj)[["Predictor"]], seq.int(sobj$p))
expect_equal(tidy_lambda(sobj)[["lambda"]][2], exp(-sobj$gamma))
expect_true(all(tidy_lambda(sobj)[["lambda"]] > 0))
})
test_that("Test tidy lambda sample.", {
expect_equal(tidy_lambda(sobj, use_population = FALSE)[["Predictor"]], seq.int(sobj$p))
expect_true(all(tidy_lambda(sobj, use_population = FALSE)[["lambda"]] > 0))
testthat::skip_on_cran()
expect_equal(tidy_lambda(sobj, use_population = FALSE)[["lambda"]][2], 0.3931997, tolerance = 1e-5)
})
test_that("Test tidy sigma.", {
testthat::skip_on_cran()
expect_equal(tidy_sigma(cov_zy)[["Covariance"]][1], -0.3761589, tolerance = 1e-5)
expect_equal(tidy_sigma(cov_xy)[["Covariance"]][1], 0.09483724, tolerance = 1e-5)
})
test_that("Test Covariance Matrices", {
expect_equal(sum(abs(cov_zw(sobj)) > 0), length(unlist(sobj$relpos)))
expect_equal(nrow(cov_zw(sobj)), sobj$p)
expect_equal(ncol(cov_zw(sobj)), sobj$m)
expect_equal(nrow(cov_zy(sobj)), sobj$p)
expect_equal(ncol(cov_zy(sobj)), sobj$m)
expect_equal(nrow(cov_xy(sobj)), sobj$p)
expect_equal(ncol(cov_xy(sobj)), sobj$m)
})
test_that("Test Sample Covariance Matrices.", {
expect_equal(nrow(cov_zy(sobj, use_population = FALSE)), sobj$p)
expect_equal(ncol(cov_zy(sobj, use_population = FALSE)), sobj$m)
expect_equal(nrow(cov_xy(sobj, use_population = FALSE)), sobj$p)
expect_equal(ncol(cov_xy(sobj, use_population = FALSE)), sobj$m)
testthat::skip_on_cran()
expect_equal(cov_zy(sobj, use_population = FALSE)[1], 0.8582035, tolerance = 1e-5)
expect_equal(cov_xy(sobj, use_population = FALSE)[1], 0.1800116, tolerance = 1e-5)
})
test_that("Absolute Covariances.", {
expect_true(all(abs_sigma(tidy_sigma(cov_xy))[["Covariance"]] >= 0))
expect_true(all(abs_sigma(tidy_sigma(cov_zy))[["Covariance"]] >= 0))
})
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