R version 4.5.0 beta (2025-03-27 r88067 ucrt) -- "How About a Twenty-Six"
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Platform: x86_64-w64-mingw32/x64

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> library(GeneralizedHyperbolic)
> data(ghypParam)
> 
> test.ghypMean <- function(testParam = ghypSmallShape, n = 10000,
+                           accuracy = 0.01) {
+   for (i in 1:nrow(testParam)) {
+     param <- testParam[i, ]
+ 
+     # random number generation:
+     x <- rghyp(n, param = param)
+ 
+     # Compute mean of the sample data:
+     sampleMean <- mean(x)
+ 
+     # Get mean value from vgMean function:
+     funMean <- ghypMean(param = param)
+ 
+     # Precision within the accuracy value?
+     difference <- abs(sampleMean - funMean)
+     cat("param", sep = "\n")
+     print(param)
+     cat("sample mean", sep = "\n")
+     print(sampleMean)
+     cat("function mean", sep = "\n")
+     print(funMean)
+     cat("difference", sep = "\n")
+     print(difference)
+     cat("checkTrue", sep = "\n")
+     print(checkTrue("test.ghypMean", difference < accuracy))
+   }
+ }
> 
> 
> test.ghypVar <- function(testParam = ghypSmallShape, n = 10000,
+                          accuracy = 0.01) {
+   for (i in 1:nrow(testParam)) {
+     param <- testParam[i, ]
+ 
+     # random number generation:
+     x <- rghyp(n, param = param)
+ 
+     # Compute variance of the sample data:
+     sampleVar <- var(x)
+ 
+     # Get mean value from vgVar function:
+     funVar <- ghypVar(param = param)
+ 
+     # Precision within the accuracy value?
+     difference <- abs(sampleVar - funVar)
+     cat("param", sep = "\n")
+     print(param)
+     cat("sample variance", sep = "\n")
+     print(sampleVar)
+     cat("function variance", sep = "\n")
+     print(funVar)
+     cat("difference", sep = "\n")
+     print(difference)
+     cat("checkTrue", sep = "\n")
+     print(checkTrue("test.ghypVar", difference < accuracy))
+   }
+ }
> 
> test.ghypSkew <- function(testParam = ghypSmallShape, n = 10000,
+                           accuracy = 0.01) {
+   for (i in 1:nrow(testParam)) {
+     param <- testParam[i, ]
+ 
+     # random number generation:
+     x <- rghyp(n, param = param)
+ 
+     # Compute skewness of the sample data:
+     sampleSkew <- DistributionUtils::skewness(x)
+ 
+     # Get skewness value from vgSkew function:
+     funSkew <- ghypSkew(param = param)
+ 
+     # Precision within the accuracy value?
+     difference <- abs(sampleSkew - funSkew)
+     cat("param", sep = "\n")
+     print(param)
+     cat("sample skewness", sep = "\n")
+     print(sampleSkew)
+     cat("function skewness", sep = "\n")
+     print(funSkew)
+     cat("difference", sep = "\n")
+     print(difference)
+     cat("checkTrue", sep = "\n")
+     print(checkTrue("test.ghypSkew", difference < accuracy))
+   }
+ }
> 
> test.ghypKurt <- function(testParam = ghypSmallShape, n = 10000,
+                           accuracy = 0.01) {
+   for (i in 1:nrow(testParam)) {
+     param <- testParam[i, ]
+ 
+     # random number generation:
+     x <- rghyp(n, param = param)
+ 
+     # Compute kurtosis of the sample data:
+     sampleKurt <- DistributionUtils::kurtosis(x)
+ 
+     # Get kurtosis value from vgKurt function:
+     funKurt <- ghypKurt(param = param)
+ 
+     # Precision within the accuracy value?
+     difference <- abs(sampleKurt - funKurt)
+     cat("param", sep = "\n")
+     print(param)
+     cat("sample kurtosis", sep = "\n")
+     print(sampleKurt)
+     cat("function kurtosis", sep = "\n")
+     print(funKurt)
+     cat("difference", sep = "\n")
+     print(difference)
+     cat("checkTrue", sep = "\n")
+     print(checkTrue("test.ghypKurt", difference < accuracy))
+   }
+ }
> 
> checkTrue <- function(f, bool) {
+   if (bool) {
+     paste(f, ": PASS", sep = "")
+   } else {
+     paste(f, ": FAIL", sep = "")
+   }
+ }
> 
> test.ghypMean()
param
[1]  0.0  1.0 99.0  0.0 -0.5
sample mean
[1] -7.009881e-05
function mean
[1] 0
difference
[1] 7.009881e-05
checkTrue
[1] "test.ghypMean: PASS"
param
[1]  0  1 99  0  0
sample mean
[1] -0.0001660476
function mean
[1] 0
difference
[1] 0.0001660476
checkTrue
[1] "test.ghypMean: PASS"
param
[1]  0  1 99  0  1
sample mean
[1] -0.001236117
function mean
[1] 0
difference
[1] 0.001236117
checkTrue
[1] "test.ghypMean: PASS"
param
[1]   0.000   1.000  18.292 -15.243  -0.500
sample mean
[1] -1.507956
function mean
[1] -1.507449
difference
[1] 0.0005075112
checkTrue
[1] "test.ghypMean: PASS"
param
[1]   0.000   1.000  18.292 -15.243   0.000
sample mean
[1] -1.575174
function mean
[1] -1.580304
difference
[1] 0.005129937
checkTrue
[1] "test.ghypMean: PASS"
param
[1]   0.000   1.000  18.292 -15.243   1.000
sample mean
[1] -1.736481
function mean
[1] -1.736109
difference
[1] 0.0003719788
checkTrue
[1] "test.ghypMean: PASS"
param
[1]  0.000  1.000 18.292 15.243 -0.500
sample mean
[1] 1.519947
function mean
[1] 1.507449
difference
[1] 0.01249853
checkTrue
[1] "test.ghypMean: FAIL"
param
[1]  0.000  1.000 18.292 15.243  0.000
sample mean
[1] 1.572694
function mean
[1] 1.580304
difference
[1] 0.007610263
checkTrue
[1] "test.ghypMean: PASS"
param
[1]  0.000  1.000 18.292 15.243  1.000
sample mean
[1] 1.732774
function mean
[1] 1.736109
difference
[1] 0.003335383
checkTrue
[1] "test.ghypMean: PASS"
param
[1]  0.000  1.000  2.804 -2.604 -0.500
sample mean
[1] -2.518914
function mean
[1] -2.503846
difference
[1] 0.01506781
checkTrue
[1] "test.ghypMean: FAIL"
param
[1]  0.000  1.000  2.804 -2.604  0.000
sample mean
[1] -3.543107
function mean
[1] -3.542298
difference
[1] 0.0008091075
checkTrue
[1] "test.ghypMean: PASS"
param
[1]  0.000  1.000  2.804 -2.604  1.000
sample mean
[1] -6.594413
function mean
[1] -6.584913
difference
[1] 0.009499973
checkTrue
[1] "test.ghypMean: PASS"
param
[1]  0.000  1.000  1.152 -0.494 -0.500
sample mean
[1] -0.468839
function mean
[1] -0.474678
difference
[1] 0.005838993
checkTrue
[1] "test.ghypMean: PASS"
param
[1]  0.000  1.000  1.152 -0.494  0.000
sample mean
[1] -0.651559
function mean
[1] -0.6714271
difference
[1] 0.01986811
checkTrue
[1] "test.ghypMean: FAIL"
param
[1]  0.000  1.000  1.152 -0.494  1.000
sample mean
[1] -1.273551
function mean
[1] -1.247806
difference
[1] 0.02574463
checkTrue
[1] "test.ghypMean: FAIL"
param
[1]  0.000  1.000  1.152  0.494 -0.500
sample mean
[1] 0.4880586
function mean
[1] 0.474678
difference
[1] 0.01338067
checkTrue
[1] "test.ghypMean: FAIL"
param
[1] 0.000 1.000 1.152 0.494 0.000
sample mean
[1] 0.6676872
function mean
[1] 0.6714271
difference
[1] 0.003739983
checkTrue
[1] "test.ghypMean: PASS"
param
[1] 0.000 1.000 1.152 0.494 1.000
sample mean
[1] 1.263879
function mean
[1] 1.247806
difference
[1] 0.01607301
checkTrue
[1] "test.ghypMean: FAIL"
param
[1]  0.000  1.000  2.804  2.604 -0.500
sample mean
[1] 2.511579
function mean
[1] 2.503846
difference
[1] 0.007733167
checkTrue
[1] "test.ghypMean: PASS"
param
[1] 0.000 1.000 2.804 2.604 0.000
sample mean
[1] 3.594437
function mean
[1] 3.542298
difference
[1] 0.05213836
checkTrue
[1] "test.ghypMean: FAIL"
param
[1] 0.000 1.000 2.804 2.604 1.000
sample mean
[1] 6.544591
function mean
[1] 6.584913
difference
[1] 0.0403223
checkTrue
[1] "test.ghypMean: FAIL"
> test.ghypVar()
param
[1]  0.0  1.0 99.0  0.0 -0.5
sample variance
[1] 0.01017173
function variance
[1] 0.01010101
difference
[1] 7.072132e-05
checkTrue
[1] "test.ghypVar: PASS"
param
[1]  0  1 99  0  0
sample variance
[1] 0.01010813
function variance
[1] 0.0101519
difference
[1] 4.376645e-05
checkTrue
[1] "test.ghypVar: PASS"
param
[1]  0  1 99  0  1
sample variance
[1] 0.01005265
function variance
[1] 0.01025444
difference
[1] 0.0002017853
checkTrue
[1] "test.ghypVar: PASS"
param
[1]   0.000   1.000  18.292 -15.243  -0.500
sample variance
[1] 0.3168646
function variance
[1] 0.3236226
difference
[1] 0.006757997
checkTrue
[1] "test.ghypVar: PASS"
param
[1]   0.000   1.000  18.292 -15.243   0.000
sample variance
[1] 0.3569074
function variance
[1] 0.349894
difference
[1] 0.007013423
checkTrue
[1] "test.ghypVar: PASS"
param
[1]   0.000   1.000  18.292 -15.243   1.000
sample variance
[1] 0.3980738
function variance
[1] 0.4074875
difference
[1] 0.009413656
checkTrue
[1] "test.ghypVar: PASS"
param
[1]  0.000  1.000 18.292 15.243 -0.500
sample variance
[1] 0.3164891
function variance
[1] 0.3236226
difference
[1] 0.007133423
checkTrue
[1] "test.ghypVar: PASS"
param
[1]  0.000  1.000 18.292 15.243  0.000
sample variance
[1] 0.3485801
function variance
[1] 0.349894
difference
[1] 0.001313922
checkTrue
[1] "test.ghypVar: PASS"
param
[1]  0.000  1.000 18.292 15.243  1.000
sample variance
[1] 0.4114046
function variance
[1] 0.4074875
difference
[1] 0.003917163
checkTrue
[1] "test.ghypVar: PASS"
param
[1]  0.000  1.000  2.804 -2.604 -0.500
sample variance
[1] 7.136556
function variance
[1] 6.989659
difference
[1] 0.1468966
checkTrue
[1] "test.ghypVar: FAIL"
param
[1]  0.000  1.000  2.804 -2.604  0.000
sample variance
[1] 12.49502
function variance
[1] 12.13818
difference
[1] 0.3568382
checkTrue
[1] "test.ghypVar: FAIL"
param
[1]  0.000  1.000  2.804 -2.604  1.000
sample variance
[1] 27.58086
function variance
[1] 28.85082
difference
[1] 1.269959
checkTrue
[1] "test.ghypVar: FAIL"
param
[1]  0.000  1.000  1.152 -0.494 -0.500
sample variance
[1] 1.175963
function variance
[1] 1.177393
difference
[1] 0.001429704
checkTrue
[1] "test.ghypVar: PASS"
param
[1]  0.000  1.000  1.152 -0.494  0.000
sample variance
[1] 1.765252
function variance
[1] 1.746161
difference
[1] 0.01909182
checkTrue
[1] "test.ghypVar: FAIL"
param
[1]  0.000  1.000  1.152 -0.494  1.000
sample variance
[1] 3.404908
function variance
[1] 3.470778
difference
[1] 0.06587049
checkTrue
[1] "test.ghypVar: FAIL"
param
[1]  0.000  1.000  1.152  0.494 -0.500
sample variance
[1] 1.245546
function variance
[1] 1.177393
difference
[1] 0.06815371
checkTrue
[1] "test.ghypVar: FAIL"
param
[1] 0.000 1.000 1.152 0.494 0.000
sample variance
[1] 1.762561
function variance
[1] 1.746161
difference
[1] 0.01640089
checkTrue
[1] "test.ghypVar: FAIL"
param
[1] 0.000 1.000 1.152 0.494 1.000
sample variance
[1] 3.463798
function variance
[1] 3.470778
difference
[1] 0.006980502
checkTrue
[1] "test.ghypVar: PASS"
param
[1]  0.000  1.000  2.804  2.604 -0.500
sample variance
[1] 6.941218
function variance
[1] 6.989659
difference
[1] 0.04844132
checkTrue
[1] "test.ghypVar: FAIL"
param
[1] 0.000 1.000 2.804 2.604 0.000
sample variance
[1] 11.78913
function variance
[1] 12.13818
difference
[1] 0.3490496
checkTrue
[1] "test.ghypVar: FAIL"
param
[1] 0.000 1.000 2.804 2.604 1.000
sample variance
[1] 28.48463
function variance
[1] 28.85082
difference
[1] 0.3661829
checkTrue
[1] "test.ghypVar: FAIL"
> test.ghypSkew()
param
[1]  0.0  1.0 99.0  0.0 -0.5
sample skewness
[1] -0.03492518
function skewness
[1] 0
difference
[1] 0.03492518
checkTrue
[1] "test.ghypSkew: FAIL"
param
[1]  0  1 99  0  0
sample skewness
[1] -0.0048763
function skewness
[1] 0
difference
[1] 0.0048763
checkTrue
[1] "test.ghypSkew: PASS"
param
[1]  0  1 99  0  1
sample skewness
[1] -0.004553416
function skewness
[1] 0
difference
[1] 0.004553416
checkTrue
[1] "test.ghypSkew: PASS"
param
[1]   0.000   1.000  18.292 -15.243  -0.500
sample skewness
[1] -0.8327693
function skewness
[1] -0.7861702
difference
[1] 0.04659913
checkTrue
[1] "test.ghypSkew: FAIL"
param
[1]   0.000   1.000  18.292 -15.243   0.000
sample skewness
[1] -0.8553135
function skewness
[1] -0.781198
difference
[1] 0.07411556
checkTrue
[1] "test.ghypSkew: FAIL"
param
[1]   0.000   1.000  18.292 -15.243   1.000
sample skewness
[1] -0.7890551
function skewness
[1] -0.7675085
difference
[1] 0.0215466
checkTrue
[1] "test.ghypSkew: FAIL"
param
[1]  0.000  1.000 18.292 15.243 -0.500
sample skewness
[1] 0.7857003
function skewness
[1] 0.7861702
difference
[1] 0.0004699127
checkTrue
[1] "test.ghypSkew: PASS"
param
[1]  0.000  1.000 18.292 15.243  0.000
sample skewness
[1] 0.8237127
function skewness
[1] 0.781198
difference
[1] 0.04251474
checkTrue
[1] "test.ghypSkew: FAIL"
param
[1]  0.000  1.000 18.292 15.243  1.000
sample skewness
[1] 0.7402046
function skewness
[1] 0.7675085
difference
[1] 0.02730393
checkTrue
[1] "test.ghypSkew: FAIL"
param
[1]  0.000  1.000  2.804 -2.604 -0.500
sample skewness
[1] -2.780241
function skewness
[1] -2.731917
difference
[1] 0.0483236
checkTrue
[1] "test.ghypSkew: FAIL"
param
[1]  0.000  1.000  2.804 -2.604  0.000
sample skewness
[1] -2.396644
function skewness
[1] -2.371095
difference
[1] 0.0255493
checkTrue
[1] "test.ghypSkew: FAIL"
param
[1]  0.000  1.000  2.804 -2.604  1.000
sample skewness
[1] -1.692121
function skewness
[1] -1.759638
difference
[1] 0.067517
checkTrue
[1] "test.ghypSkew: FAIL"
param
[1]  0.000  1.000  1.152 -0.494 -0.500
sample skewness
[1] -1.06623
function skewness
[1] -1.261049
difference
[1] 0.194818
checkTrue
[1] "test.ghypSkew: FAIL"
param
[1]  0.000  1.000  1.152 -0.494  0.000
sample skewness
[1] -1.294245
function skewness
[1] -1.277531
difference
[1] 0.01671359
checkTrue
[1] "test.ghypSkew: FAIL"
param
[1]  0.000  1.000  1.152 -0.494  1.000
sample skewness
[1] -1.131408
function skewness
[1] -1.142286
difference
[1] 0.01087842
checkTrue
[1] "test.ghypSkew: FAIL"
param
[1]  0.000  1.000  1.152  0.494 -0.500
sample skewness
[1] 1.258553
function skewness
[1] 1.261049
difference
[1] 0.002495056
checkTrue
[1] "test.ghypSkew: PASS"
param
[1] 0.000 1.000 1.152 0.494 0.000
sample skewness
[1] 1.259126
function skewness
[1] 1.277531
difference
[1] 0.01840484
checkTrue
[1] "test.ghypSkew: FAIL"
param
[1] 0.000 1.000 1.152 0.494 1.000
sample skewness
[1] 1.338078
function skewness
[1] 1.142286
difference
[1] 0.195792
checkTrue
[1] "test.ghypSkew: FAIL"
param
[1]  0.000  1.000  2.804  2.604 -0.500
sample skewness
[1] 2.647284
function skewness
[1] 2.731917
difference
[1] 0.08463364
checkTrue
[1] "test.ghypSkew: FAIL"
param
[1] 0.000 1.000 2.804 2.604 0.000
sample skewness
[1] 2.278711
function skewness
[1] 2.371095
difference
[1] 0.09238381
checkTrue
[1] "test.ghypSkew: FAIL"
param
[1] 0.000 1.000 2.804 2.604 1.000
sample skewness
[1] 1.764065
function skewness
[1] 1.759638
difference
[1] 0.004426242
checkTrue
[1] "test.ghypSkew: PASS"
> test.ghypKurt()
param
[1]  0.0  1.0 99.0  0.0 -0.5
sample kurtosis
[1] 0.008844819
function kurtosis
[1] 0.03030303
difference
[1] 0.02145821
checkTrue
[1] "test.ghypKurt: FAIL"
param
[1]  0  1 99  0  0
sample kurtosis
[1] 0.07450673
function kurtosis
[1] 0.03030189
difference
[1] 0.04420484
checkTrue
[1] "test.ghypKurt: FAIL"
param
[1]  0  1 99  0  1
sample kurtosis
[1] -0.01235892
function kurtosis
[1] 0.03029735
difference
[1] 0.04265627
checkTrue
[1] "test.ghypKurt: FAIL"
param
[1]   0.000   1.000  18.292 -15.243  -0.500
sample kurtosis
[1] 0.9517493
function kurtosis
[1] 1.120768
difference
[1] 0.169019
checkTrue
[1] "test.ghypKurt: FAIL"
param
[1]   0.000   1.000  18.292 -15.243   0.000
sample kurtosis
[1] 0.9552408
function kurtosis
[1] 1.094295
difference
[1] 0.1390537
checkTrue
[1] "test.ghypKurt: FAIL"
param
[1]   0.000   1.000  18.292 -15.243   1.000
sample kurtosis
[1] 1.073529
function kurtosis
[1] 1.034318
difference
[1] 0.03921088
checkTrue
[1] "test.ghypKurt: FAIL"
param
[1]  0.000  1.000 18.292 15.243 -0.500
sample kurtosis
[1] 0.7598373
function kurtosis
[1] 1.120768
difference
[1] 0.360931
checkTrue
[1] "test.ghypKurt: FAIL"
param
[1]  0.000  1.000 18.292 15.243  0.000
sample kurtosis
[1] 1.063998
function kurtosis
[1] 1.094295
difference
[1] 0.03029657
checkTrue
[1] "test.ghypKurt: FAIL"
param
[1]  0.000  1.000 18.292 15.243  1.000
sample kurtosis
[1] 1.157864
function kurtosis
[1] 1.034318
difference
[1] 0.1235461
checkTrue
[1] "test.ghypKurt: FAIL"
param
[1]  0.000  1.000  2.804 -2.604 -0.500
sample kurtosis
[1] 10.1795
function kurtosis
[1] 12.83578
difference
[1] 2.656279
checkTrue
[1] "test.ghypKurt: FAIL"
param
[1]  0.000  1.000  2.804 -2.604  0.000
sample kurtosis
[1] 7.733898
function kurtosis
[1] 9.209436
difference
[1] 1.475538
checkTrue
[1] "test.ghypKurt: FAIL"
param
[1]  0.000  1.000  2.804 -2.604  1.000
sample kurtosis
[1] 3.840174
function kurtosis
[1] 4.804167
difference
[1] 0.9639928
checkTrue
[1] "test.ghypKurt: FAIL"
param
[1]  0.000  1.000  1.152 -0.494 -0.500
sample kurtosis
[1] 4.341496
function kurtosis
[1] 5.002984
difference
[1] 0.6614881
checkTrue
[1] "test.ghypKurt: FAIL"
param
[1]  0.000  1.000  1.152 -0.494  0.000
sample kurtosis
[1] 3.251463
function kurtosis
[1] 4.426761
difference
[1] 1.175298
checkTrue
[1] "test.ghypKurt: FAIL"
param
[1]  0.000  1.000  1.152 -0.494  1.000
sample kurtosis
[1] 2.448337
function kurtosis
[1] 2.992638
difference
[1] 0.5443014
checkTrue
[1] "test.ghypKurt: FAIL"
param
[1]  0.000  1.000  1.152  0.494 -0.500
sample kurtosis
[1] 4.637385
function kurtosis
[1] 5.002984
difference
[1] 0.3655993
checkTrue
[1] "test.ghypKurt: FAIL"
param
[1] 0.000 1.000 1.152 0.494 0.000
sample kurtosis
[1] 5.045537
function kurtosis
[1] 4.426761
difference
[1] 0.6187767
checkTrue
[1] "test.ghypKurt: FAIL"
param
[1] 0.000 1.000 1.152 0.494 1.000
sample kurtosis
[1] 3.659032
function kurtosis
[1] 2.992638
difference
[1] 0.6663941
checkTrue
[1] "test.ghypKurt: FAIL"
param
[1]  0.000  1.000  2.804  2.604 -0.500
sample kurtosis
[1] 8.426895
function kurtosis
[1] 12.83578
difference
[1] 4.408884
checkTrue
[1] "test.ghypKurt: FAIL"
param
[1] 0.000 1.000 2.804 2.604 0.000
sample kurtosis
[1] 7.693842
function kurtosis
[1] 9.209436
difference
[1] 1.515594
checkTrue
[1] "test.ghypKurt: FAIL"
param
[1] 0.000 1.000 2.804 2.604 1.000
sample kurtosis
[1] 5.451786
function kurtosis
[1] 4.804167
difference
[1] 0.6476189
checkTrue
[1] "test.ghypKurt: FAIL"
> 
> proc.time()
   user  system elapsed 
   5.32    0.12    5.39