context("Discover Distributions - F distribution")
options <- jaspTools::analysisOptions("LDf")
options$.meta <- list(newVariableName = list(containsColumn = TRUE), variable = list(
containsColumn = TRUE))
options$andersonDarling <- TRUE
options$ciInterval <- TRUE
options$ciIntervalInterval <- 0.95
options$cramerVonMisses <- TRUE
options$ecdf <- TRUE
options$estCDF <- TRUE
options$estPDF <- TRUE
options$explanatoryText <- TRUE
options$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$parsSupportMoments <- TRUE
options$plotCDF <- TRUE
options$plotQF <- TRUE
options$ppplot <- TRUE
options$qqplot <- TRUE
options$qqPlotCi <- FALSE
options$qqPlotCiLevel <- 0.95
options$ppPlotCi <- FALSE
options$ppPlotCiLevel <- 0.95
options$summary <- TRUE
options$variable <- "F1000(df1=5,df2=5,ncp=0)"
set.seed(1)
results <- jaspTools::runAnalysis("LDf", "Distributions.csv", 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(1.67051432111236, 1, 1.67051432111236, 5.09245987979049, 2, 7.88307797683197
))
})
test_that("Descriptives table results match", {
table <- results[["results"]][["dataContainer"]][["collection"]][["dataContainer_summary"]][["data"]]
jaspTools::expect_equal_tables(table,
list(33.6508909853388, 1.67051432111236, 1.01878902269919, 0.014610127951185,
0.533763088779671, 1.90650607669046, 1000, 2.25777710087327,
5.09755743722772, "F1000(df1=5,df2=5,ncp=0)"))
})
test_that("Estimated Parameters table results match", {
table <- results[["results"]][["mleContainer"]][["collection"]][["mleContainer_estParametersTable"]][["data"]]
jaspTools::expect_equal_tables(table,
list(5.43367102099383, 4.31732574348814, "df 1", 0.569574383157694,
6.55001629849953, 4.90464837342639, 3.98863373749554, "df 2",
0.467362993991856, 5.82066300935723, 0.0336173756256012, -0.461124178873562,
"ncp", 0.252423798805295, 0.528358930124764))
})
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(0.996070666453852, 0.0129551754522244, "Kolmogorov-Smirnov", 0,
0, 0, 0.796463354892749, 0.464063438492745, "Cram<unicode>r-von Mises",
0, 0, 0, 0.113388388344629, 4.77310436276239, "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")
})
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.