context("Discover Distributions - Scaled, shifted Student's t-distribution")
options <- jaspTools::analysisOptions("LDtStudent")
options$plotPDF <- TRUE
options$plotCDF <- TRUE
options$plotQF <- TRUE
options$df <- 1.5
options$location <- -1
options$scale <- 0.7
options$andersonDarling <- TRUE
options$ciInterval <- TRUE
options$ciIntervalInterval <- 0.95
options$cramerVonMisses <- TRUE
options$ecdf <- TRUE
options$estCDF <- TRUE
options$estPDF <- TRUE
options$highlightDensity <- TRUE
options$highlightProbability <- TRUE
options$histogram <- TRUE
options$kolmogorovSmirnov <- TRUE
options$methodMLE <- TRUE
options$moments <- TRUE
options$newVariableName <- ""
options$outputEstimates <- TRUE
options$outputSE <- TRUE
options$ppplot <- TRUE
options$qqplot <- TRUE
options$qqPlotCi <- FALSE
options$qqPlotCiLevel <- 0.95
options$ppPlotCi <- FALSE
options$ppPlotCiLevel <- 0.95
options$summary <- TRUE
options$variable <- "tStudent"
set.seed(1)
results <- jaspTools::runAnalysis("LDtStudent",
data.frame(tStudent = jaspDistributions:::rtscaledshifted(n=100, df=3, location=-1, scale=2)),
options)
test_that("Empirical Cumulative Distribution plot matches", {
plotName <- results[["results"]][["dataContainer"]][["collection"]][["dataContainer_ecdf"]][["data"]]
testPlot <- results[["state"]][["figures"]][[plotName]][["obj"]]
jaspTools::expect_equal_plots(testPlot, "empirical-cumulative-distribution")
})
test_that("Histogram plot matches", {
plotName <- results[["results"]][["dataContainer"]][["collection"]][["dataContainer_histogram"]][["data"]]
testPlot <- results[["state"]][["figures"]][[plotName]][["obj"]]
jaspTools::expect_equal_plots(testPlot, "histogram")
})
test_that("Observed Moments table results match", {
table <- results[["results"]][["dataContainer"]][["collection"]][["dataContainer_moments"]][["data"]]
jaspTools::expect_equal_tables(table,
list(-0.655560734200281, 1, -0.655560734200281, 9.65934924276094, 2,
10.0891091189861))
})
test_that("Descriptives table results match", {
table <- results[["results"]][["dataContainer"]][["collection"]][["dataContainer_summary"]][["data"]]
jaspTools::expect_equal_tables(table,
list(10.3733530599464, -0.655560734200281, -0.718015195627216, -12.8514065738538,
-2.37931993595805, 1.10294531587972, 100, 3.12360663769164,
9.75691842703126, "tStudent"))
})
test_that("Estimated Parameters table results match", {
table <- results[["results"]][["mleContainer"]][["collection"]][["mleContainer_estParametersTable"]][["data"]]
jaspTools::expect_equal_tables(table,
list(3.41378880000688, 0.898187570340698, "df", 1.28349359963189, 5.92939002967305,
-0.631403218583005, -1.13350202888241, "<unicode>", 0.256177569720616,
-0.129304408283599, 2.12705610205016, 1.58348934485134, "<unicode>",
0.27733507425973, 2.67062285924897))
})
test_that("Empirical vs. Theoretical CDF plot matches", {
plotName <- results[["results"]][["mleContainer"]][["collection"]][["mleContainer_mleFitAssessment"]][["collection"]][["mleContainer_mleFitAssessment_estCDF"]][["data"]]
testPlot <- results[["state"]][["figures"]][[plotName]][["obj"]]
jaspTools::expect_equal_plots(testPlot, "empirical-vs-theoretical-cdf")
})
test_that("Histogram vs. Theoretical PDF plot matches", {
plotName <- results[["results"]][["mleContainer"]][["collection"]][["mleContainer_mleFitAssessment"]][["collection"]][["mleContainer_mleFitAssessment_estPDF"]][["data"]]
testPlot <- results[["state"]][["figures"]][[plotName]][["obj"]]
jaspTools::expect_equal_plots(testPlot, "histogram-vs-theoretical-pdf")
})
test_that("Fit Statistics table results match", {
table <- results[["results"]][["mleContainer"]][["collection"]][["mleContainer_mleFitAssessment"]][["collection"]][["mleContainer_mleFitAssessment_fitStatisticsTable"]][["data"]]
jaspTools::expect_equal_tables(table,
list(0.999402650966449, 0.0363149613211432, "Kolmogorov-Smirnov", 0,
0, 0, 0.51083515626586, 0.403161408295653, "Cram<unicode>r-von Mises",
0, 0, 0, 0.409703308608111, 2.49030408145177, "Anderson-Darling"
))
})
test_that("P-P plot matches", {
plotName <- results[["results"]][["mleContainer"]][["collection"]][["mleContainer_mleFitAssessment"]][["collection"]][["mleContainer_mleFitAssessment_ppplot"]][["data"]]
testPlot <- results[["state"]][["figures"]][[plotName]][["obj"]]
jaspTools::expect_equal_plots(testPlot, "p-p-plot")
})
test_that("Q-Q plot matches", {
plotName <- results[["results"]][["mleContainer"]][["collection"]][["mleContainer_mleFitAssessment"]][["collection"]][["mleContainer_mleFitAssessment_qqplot"]][["data"]]
testPlot <- results[["state"]][["figures"]][[plotName]][["obj"]]
jaspTools::expect_equal_plots(testPlot, "q-q-plot")
})
test_that("Cumulative Probability Plot matches", {
plotName <- results[["results"]][["plotCDF"]][["collection"]][["plotCDF_cdfPlot"]][["data"]]
testPlot <- results[["state"]][["figures"]][[plotName]][["obj"]]
jaspTools::expect_equal_plots(testPlot, "cumulative-probability-plot")
})
test_that("Density Plot matches", {
plotName <- results[["results"]][["plotPDF"]][["collection"]][["plotPDF_pdfPlot"]][["data"]]
testPlot <- results[["state"]][["figures"]][[plotName]][["obj"]]
jaspTools::expect_equal_plots(testPlot, "density-plot")
})
test_that("Quantile Plot matches", {
plotName <- results[["results"]][["plotQF"]][["collection"]][["plotQF_qfPlot"]][["data"]]
testPlot <- results[["state"]][["figures"]][[plotName]][["obj"]]
jaspTools::expect_equal_plots(testPlot, "quantile-plot")
})
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