Running ‘doRUnit.R’ [13s/56s]
Running the tests in ‘tests/doRUnit.R’ failed.
Complete output:
  > #### doRUnit.R --- Run RUnit tests
  > ####------------------------------------------------------------------------
  > 
  > ### Origianlly follows Gregor Gojanc's example in CRAN package  'gdata'
  > ### and the corresponding section in the R Wiki:
  > ###  http://wiki.r-project.org/rwiki/doku.php?id=developers:runit
  > 
  > ### MM: Vastly changed:  This should also be "runnable" for *installed*
  > ##              package which has no ./tests/
  > ## ----> put the bulk of the code e.g. in  ../inst/unitTests/runTests.R :
  > 
  > if(require("RUnit", quietly=TRUE)) {
  + 
  +   ## --- Setup ---
  + 
  +   wd <- getwd()
  +   pkg <- sub("\\.Rcheck$", '', basename(dirname(wd)))
  + 
  +   library(package=pkg, character.only=TRUE)
  + 
  +   path <- system.file("unitTests", package = pkg)
  + 
  +   stopifnot(file.exists(path), file.info(path.expand(path))$isdir)
  + 
  +   source(file.path(path, "runTests.R"), echo = TRUE)
  + }
  
  > pkg <- "fBasics"
  
  > if (require("RUnit", quietly = TRUE)) {
  +     library(package = pkg, character.only = TRUE)
  +     if (!(exists("path") && file.exists(path))) 
  +     .... [TRUNCATED] 
  
  
  Executing test function test.ghFit  ... 
  Title:
   Generalized Hyperbolic Parameter Estimation 
  
  Call:
   ghFit(x = s, alpha = 1, beta = 0, delta = 1, mu = 0, lambda = 1, 
      trace = FALSE)
  
  Model:
   Generalized Hyperbolic Distribution
  
  Estimated Parameter(s):
       alpha       beta      delta         mu     lambda 
   0.9756821  0.2232877  1.6766496 -0.4420942  1.9206148 
  
   alpha   beta  delta     mu lambda 
   FALSE  FALSE   TRUE  FALSE   TRUE 
   done successfully.
  
  
  
  Executing test function test.hypFit  ... 
  Title:
   Hyperbolic Parameter Estimation 
  
  Call:
   hypFit(x = s, alpha = 1, beta = 0, delta = 1, mu = mean(s), trace = FALSE)
  
  Model:
   Hyperbolic Distribution
  
  Estimated Parameter(s):
       alpha       beta      delta         mu 
   1.5729454  0.8564488  0.6353837 -1.0490652 
  
  alpha  beta delta    mu 
   TRUE  TRUE FALSE  TRUE 
   done successfully.
  
  
  
  Executing test function test.nFit  ... nFit():
  
  Title:
   Normal Parameter Estimation 
  
  Call:
   nFit(x = s)
  
  Model:
   Normal Distribution
  
  Estimated Parameter(s):
       mean        sd 
  1.0021968 0.5079231 
  
  mean   sd 
  TRUE TRUE 
   done successfully.
  
  
  
  Executing test function test.nigFit  ... 
  Title:
   Normal Inverse Gaussian Parameter Estimation 
  
  Call:
   .nigFit.mle(x = x, alpha = alpha, beta = beta, delta = delta, 
      mu = mu, scale = scale, doplot = doplot, span = span, trace = trace, 
      title = title, description = description)
  
  Model:
   Normal Inverse Gaussian Distribution
  
  Estimated Parameter(s):
       alpha       beta      delta         mu 
   1.8176996 -0.9248387  0.5316174 -0.9320036 
  
       alpha       beta      delta         mu 
  0.14990770 0.04105442 0.01155789        NaN 
        th.0        est         SE
  alpha  1.5  1.8176996 0.14990770
  beta  -0.7 -0.9248387 0.04105442
  delta  0.5  0.5316174 0.01155789
  mu    -1.0 -0.9320036        NaN
  t-ratios:
       alpha       beta      delta         mu 
   2.1193015 -5.4766015  2.7355709  0.6799637 
   done successfully.
  
  
  
  Executing test function test.stableFit  ... stableFit():
  
  Title:
   Stable Parameter Estimation 
  
  Call:
   .qStableFit(x = x, doplot = doplot, title = title, description = description)
  
  Model:
   Stable Distribution
  
  Estimated Parameter(s):
      alpha      beta     gamma     delta 
  1.7420000 0.2620000 1.0230413 0.2110089 
  
        th.0       est      relErr
  alpha  1.8 1.7420000 -0.03222222
  beta   0.3 0.2620000 -0.12666667
  gamma  1.0 1.0230413  0.02304133
  delta  0.1 0.2110089  1.11008893
   done successfully.
  
  
  
  Executing test function test.tFit  ... 
  Title:
   Student-t Parameter Estimation 
  
  Call:
   tFit(x = s, df = 2 * var(s)/(var(s) - 1), trace = FALSE)
  
  Model:
   Student-t Distribution
  
  Estimated Parameter(s):
        df 
  3.687089 
  
    df 
  TRUE 
   done successfully.
  
  
  
  Executing test function test.Heaviside  ...  done successfully.
  
  
  
  Executing test function test.gh  ... 
  Distribution Check for: gh 
   Call: fBasics:::.distCheck(fun = "gh", n = 2000, robust = FALSE, alpha = 1.3, 
      beta = 0.3, delta = 1.7, mu = 0.2, lambda = 0.8)
  
  1. Normalization Check:
   NORM 1 with absolute error < 3.4e-07
  
  2. [p-pfun(qfun(p))]^2 Check:
      [,1] [,2] [,3] [,4] [,5] [,6]  [,7]
  p 0.001 0.01  0.1  0.5  0.9 0.99 0.999
  P 0.001 0.01  0.1  0.5  0.9 0.99 0.999
          RMSE 
  1.011492e-06 
  
  3. r(2000) Check:
          MEAN  VAR
  SAMPLE 0.883 2.25
     X   0.8589451 with absolute error < 1.3e-05
     X^2 3.107412 with absolute error < 0.00015
          MEAN  VAR
  EXACT  0.859 2.37
  
     normCheck    rmseCheck meanvarCheck 
          TRUE         TRUE         TRUE 
   done successfully.
  
  
  
  Executing test function test.hyp  ... 
  Distribution Check for: hyp 
   Call: fBasics:::.distCheck(fun = "hyp", n = 1000, robust = FALSE, alpha = 1.2, 
      beta = 0.2, delta = 1.9, mu = 0.1, pm = "1")
  
  1. Normalization Check:
   NORM 1 with absolute error < 6e-07
  
  2. [p-pfun(qfun(p))]^2 Check:
      [,1] [,2] [,3] [,4] [,5] [,6]  [,7]
  p 0.001 0.01  0.1  0.5  0.9 0.99 0.999
  P 0.001 0.01  0.1  0.5  0.9 0.99 0.999
          RMSE 
  8.013692e-07 
  
  3. r(1000) Check:
         MEAN  VAR
  SAMPLE 0.68 2.72
     X   0.652347 with absolute error < 1.8e-05
     X^2 3.300974 with absolute error < 0.00015
          MEAN  VAR
  EXACT  0.652 2.88
  
     normCheck    rmseCheck meanvarCheck 
          TRUE         TRUE         TRUE 
  
  Distribution Check for: hyp 
   Call: fBasics:::.distCheck(fun = "hyp", n = 1000, robust = FALSE, alpha = 0.9, 
      beta = -0.3, delta = 1.4, mu = -0.1, pm = "2")
  
  1. Normalization Check:
   NORM 0.9999999 with absolute error < 1e-04
  
  2. [p-pfun(qfun(p))]^2 Check:
      [,1] [,2] [,3] [,4] [,5] [,6]  [,7]
  p 0.001 0.01  0.1  0.5  0.9 0.99 0.999
  P 0.001 0.01  0.1  0.5  0.9 0.99 0.999
          RMSE 
  1.458313e-06 
  
  3. r(1000) Check:
          MEAN VAR
  SAMPLE -1.34 7.4
     X   -1.377474 with absolute error < 1.2e-05
     X^2 9.277938 with absolute error < 6.8e-05
          MEAN  VAR
  EXACT  -1.38 7.38
  
     normCheck    rmseCheck meanvarCheck 
          TRUE         TRUE         TRUE 
  
  Distribution Check for: hyp 
   Call: fBasics:::.distCheck(fun = "hyp", n = 1000, robust = FALSE, alpha = 0.9, 
      beta = -0.3, delta = 1.4, mu = -0.1, pm = "3")
  
  1. Normalization Check:
   NORM 1 with absolute error < 4.2e-05
  
  2. [p-pfun(qfun(p))]^2 Check:
      [,1] [,2] [,3] [,4] [,5] [,6]  [,7]
  p 0.001 0.01  0.1  0.5  0.9 0.99 0.999
  P 0.001 0.01  0.1  0.5  0.9 0.99 0.999
          RMSE 
  1.667319e-07 
  
  3. r(1000) Check:
          MEAN  VAR
  SAMPLE -4.34 91.2
     X   -4.517556 with absolute error < 2.3e-05
     X^2 112.9993 with absolute error < 8e-04
          MEAN  VAR
  EXACT  -4.52 92.6
  
     normCheck    rmseCheck meanvarCheck 
          TRUE         TRUE         TRUE 
   done successfully.
  
  
  
  Executing test function test.hypSlider  ...  done successfully.
  
  
  
  Executing test function test.nig  ... 
  Distribution Check for: nig 
   Call: fBasics:::.distCheck(fun = "nig", n = 1000, robust = FALSE, alpha = 2.1, 
      beta = 0.1, delta = 1.5, mu = -0.1)
  
  1. Normalization Check:
   NORM 1 with absolute error < 3.5e-07
  
  2. [p-pfun(qfun(p))]^2 Check:
      [,1] [,2] [,3] [,4] [,5] [,6]  [,7]
  p 0.001 0.01  0.1  0.5  0.9 0.99 0.999
  P 0.001 0.01  0.1  0.5  0.9 0.99 0.999
          RMSE 
  1.163456e-06 
  
  3. r(1000) Check:
            MEAN   VAR
  SAMPLE -0.0293 0.753
     X   -0.02849031 with absolute error < 5.1e-06
     X^2 0.7175339 with absolute error < 2.9e-05
            MEAN   VAR
  EXACT  -0.0285 0.717
  
     normCheck    rmseCheck meanvarCheck 
          TRUE         TRUE         TRUE 
   done successfully.
  
  
  
  Executing test function test.nigSlider  ...  done successfully.
  
  
  
  Executing test function test.jbData  ...  done successfully.
  
  
  
  Executing test function test.jbTable  ...  done successfully.
  
  
  
  Executing test function test.NormalityTests  ... 
  Title:
   Exact one-sample Kolmogorov-Smirnov test
  
  Test Results:
    STATISTIC:
      D: 0.1074
    P VALUE:
      Alternative Two-Sided: 0.5736 
      Alternative      Less: 0.294 
      Alternative   Greater: 0.8594 
  
  
  Title:
   Shapiro - Wilk Normality Test
  
  Test Results:
    STATISTIC:
      W: 0.9746
    P VALUE:
      0.3514 
  
  
  Title:
   Jarque - Bera Normalality Test
  
  Test Results:
    STATISTIC:
      X-squared: 1.1649
    P VALUE:
      Asymptotic p Value: 0.5585 
  
  Loading required package: interp
  
  Title:
   Jarque - Bera Normality Test
  
  Test Results:
    PARAMETER:
      Sample Size: 50
    STATISTIC:
      LM: 1.165
      ALM: 1.348
    P VALUE:
      LM p-value: 0.452 
      ALM p-value: 0.424 
      Asymptotic: 0.559 
  
  
  Title:
   D'Agostino Normality Test
  
  Test Results:
    STATISTIC:
      Chi2 | Omnibus: 1.5568
      Z3  | Skewness: -1.1768
      Z4  | Kurtosis: 0.4147
    P VALUE:
      Omnibus  Test: 0.4591 
      Skewness Test: 0.2393 
      Kurtosis Test: 0.6784 
  
  
  Title:
   Anderson - Darling Normality Test
  
  Test Results:
    STATISTIC:
      A: 0.2798
    P VALUE:
      0.6307 
  
  
  Title:
   Cramer - von Mises Normality Test
  
  Test Results:
    STATISTIC:
      W: 0.0344
    P VALUE:
      0.7757 
  
  
  Title:
   Lilliefors (KS) Normality Test
  
  Test Results:
    STATISTIC:
      D: 0.0632
    P VALUE:
      0.8874 
  
  
  Title:
   Pearson Chi-Square Normality Test
  
  Test Results:
    PARAMETER:
      Number of Classes: 10
    STATISTIC:
      P: 3.6
    P VALUE:
      Adhusted: 0.8245 
      Not adjusted: 0.9357 
  
  
  Title:
   Shapiro - Francia Normality Test
  
  Test Results:
    STATISTIC:
      W: 0.9743
    P VALUE:
      0.29 
  
   done successfully.
  
  
  
  Executing test function test.NormalityTests.MSFT  ... 
  Title:
   Asymptotic one-sample Kolmogorov-Smirnov test
  
  Test Results:
    STATISTIC:
      D: 0.4541
    P VALUE:
      Alternative Two-Sided: < 2.2e-16 
      Alternative      Less: < 2.2e-16 
      Alternative   Greater: < 2.2e-16 
  
  
  Title:
   Shapiro - Wilk Normality Test
  
  Test Results:
    STATISTIC:
      W: 0.9595
    P VALUE:
      1.911e-06 
  
  
  Title:
   Jarque - Bera Normalality Test
  
  Test Results:
    STATISTIC:
      X-squared: 97.8732
    P VALUE:
      Asymptotic p Value: < 2.2e-16 
  
  
  Title:
   Jarque - Bera Normality Test
  
  Test Results:
    PARAMETER:
      Sample Size: 248
    STATISTIC:
      LM: 97.873
      ALM: 105.288
    P VALUE:
      ALM p-value: < 2.2e-16 
      Asymptotic: < 2.2e-16 
  
  
  Title:
   D'Agostino Normality Test
  
  Test Results:
    STATISTIC:
      Chi2 | Omnibus: 28.8972
      Z3  | Skewness: 2.5469
      Z4  | Kurtosis: 4.734
    P VALUE:
      Omnibus  Test: 5.309e-07 
      Skewness Test: 0.01087 
      Kurtosis Test: 2.202e-06 
  
  
  Title:
   Anderson - Darling Normality Test
  
  Test Results:
    STATISTIC:
      A: 1.5917
    P VALUE:
      0.0004206 
  
  
  Title:
   Cramer - von Mises Normality Test
  
  Test Results:
    STATISTIC:
      W: 0.195
    P VALUE:
      0.006156 
  
  
  Title:
   Lilliefors (KS) Normality Test
  
  Test Results:
    STATISTIC:
      D: 0.0559
    P VALUE:
      0.05848 
  
  
  Title:
   Pearson Chi-Square Normality Test
  
  Test Results:
    PARAMETER:
      Number of Classes: 19
    STATISTIC:
      P: 16.4677
    P VALUE:
      Adhusted: 0.4208 
      Not adjusted: 0.5599 
  
  
  Title:
   Shapiro - Francia Normality Test
  
  Test Results:
    STATISTIC:
      W: 0.9544
    P VALUE:
      2.225e-06 
  
   done successfully.
  
  
  
  Executing test function test.basicStats  ...  done successfully.
  
  
  
  Executing test function test.densityPlot  ...  done successfully.
  
  
  
  Executing test function test.distCheck  ... 
  Distribution Check for: norm 
   Call: fBasics:::.distCheck()
  
  1. Normalization Check:
   NORM 1 with absolute error < 9.4e-05
  
  2. [p-pfun(qfun(p))]^2 Check:
      [,1] [,2] [,3] [,4] [,5] [,6]  [,7]
  p 0.001 0.01  0.1  0.5  0.9 0.99 0.999
  P 0.001 0.01  0.1  0.5  0.9 0.99 0.999
          RMSE 
  2.205081e-17 
  
  3. r(1000) Check:
            MEAN   VAR
  SAMPLE 0.00861 0.799
     X   0 with absolute error < 0
     X^2 1 with absolute error < 1.2e-07
         MEAN VAR
  EXACT     0   1
  
   done successfully.
  
  
  
  Executing test function test.histPlot  ...  done successfully.
  
  
  
  Executing test function test.qqnormPlot  ...  done successfully.
  
  
  
  Executing test function test.seriesPlot  ...  done successfully.
  
  
  
  Executing test function test.stdev  ...  done successfully.
  
  
  
  Executing test function test.acfPlot  ...  done successfully.
  
  
  
  Executing test function test.lacfPlot  ...  done successfully.
  
  
  
  Executing test function test.lmacfPlot  ...  done successfully.
  
  
  
  Executing test function test.logpdfPlot  ...  done successfully.
  
  
  
  Executing test function test.pacfPlot  ...  done successfully.
  
  
  
  Executing test function test.qqgausPlot  ...  done successfully.
  
  
  
  Executing test function test.scalinglawPlot  ... 
  Scaling Law:          Open
    Plot Intercept      1.83971
    Plot Slope          0.505934
    Plot Inverse Slope  1.976542
  
  
  Scaling Law:          Open
    Plot Intercept      1.83971
    Plot Slope          0.505934
    Plot Inverse Slope  1.976542
  
   done successfully.
  
  
  
  Executing test function test.teffectPlot  ...  done successfully.
  
  
  
  Executing test function test.Sys.putenv  ...  done successfully.
  
  
  
  Executing test function test.correlationTests  ... 
  Title:
   Pearson's Correlation Test
  
  Test Results:
    PARAMETER:
      Degrees of Freedom: 98
    SAMPLE ESTIMATES:
      Correlation: 0.0845
    STATISTIC:
      t: 0.8398
    P VALUE:
      Alternative Two-Sided: 0.4031 
      Alternative      Less: 0.7985 
      Alternative   Greater: 0.2015 
    CONFIDENCE INTERVAL:
      Two-Sided: -0.1138, 0.2764
           Less: -1, 0.2466
        Greater: -0.0821, 1
  
  
  Title:
   Kendall's tau Correlation Test
  
  Test Results:
    SAMPLE ESTIMATES:
      tau: 0.042
    STATISTIC:
      z: 0.6194
      T | Exact: 2579
    P VALUE:
      Alternative         Two-Sided: 0.5356 
      Alternative Two-Sided | Exact: 0.5385 
      Alternative              Less: 0.7322 
      Alternative      Less | Exact: 0.7327 
      Alternative           Greater: 0.2678 
      Alternative   Greater | Exact: 0.2693 
  
  
  Title:
   Spearman's rho Correlation Test
  
  Test Results:
    SAMPLE ESTIMATES:
      rho: 0.0636
    STATISTIC:
      S: 156044
    P VALUE:
      Alternative Two-Sided: 0.5287 
      Alternative      Less: 0.7357 
      Alternative   Greater: 0.2643 
  
   done successfully.
  
  
  
  Executing test function test.distributionTest  ... 
  Title:
   Kolmogorov-Smirnov Two Sample Test
  
  Test Results:
    STATISTIC:
      D | Two Sided: 0.18
         D^- | Less: 0.04
      D^+ | Greater: 0.18
    P VALUE:
      Alternative       Two-Sided: 0.2222 
      Alternative Exact Two-Sided: 0.2222 
      Alternative            Less: 0.8921 
      Alternative         Greater: 0.1112 
  
   done successfully.
  
  
  
  Executing test function test.locationTests  ... 
  Title:
   t Test
  
  Test Results:
    PARAMETER:
      x Observations: 100
      y Observations: 50
      mu: 0
    SAMPLE ESTIMATES:
      Mean of x: -0.0329
      Mean of y: 0.2294
      Var  of x: 0.8731
      Var  of y: 2.0739
    STATISTIC:
                  T: -1.1705
      T | Equal Var: -1.3434
    P VALUE:
      Alternative Two-Sided: 0.2457 
      Alternative      Less: 0.1229 
      Alternative   Greater: 0.8771 
      Alternative Two-Sided | Equal Var: 0.1812 
      Alternative      Less | Equal Var: 0.0906 
      Alternative   Greater | Equal Var: 0.9094 
    CONFIDENCE INTERVAL:
      Two-Sided: -0.7092, 0.1846
           Less: -Inf, 0.1112
        Greater: -0.6358, Inf
      Two-Sided | Equal Var: -0.6481, 0.1235
           Less | Equal Var: -Inf, 0.0609
        Greater | Equal Var: -0.5855, Inf
  
  
  Title:
   Kruskal-Wallis Two Sample Test
  
  Test Results:
    PARAMETER:
      x Observations: 100
      y Observations: 50
    SAMPLE ESTIMATES:
      Mean of x: -0.0329
      Mean of y: 0.2294
      Var  of x: 0.8731
      Var  of y: 2.0739
    STATISTIC:
      KW chi-squared: 2.4175
    P VALUE:
      0.12 
  
   done successfully.
  
  
  
  Executing test function test.scaleTests  ... 
  Title:
   Ansari-Bradley Test for Scale
  
  Test Results:
    STATISTIC:
      AB: 3981
    P VALUE:
      Alternative Two-Sided        : 0.1489 
      Alternative Two-Sided | Exact: 0.1505 
      Alternative      Less        : 0.07447 
      Alternative      Less | Exact: 0.07526 
      Alternative   Greater        : 0.9255 
      Alternative   Greater | Exact: 0.9259 
    CONFIDENCE INTERVAL:
      Two-Sided | Asymptotic : 0.5762, 1.0916
      Two-Sided |      Exact : 0.5758, 1.0924
      Less      | Asymptotic : 0, 1.0416
      Less      |      Exact : 0, 1.0415
      Greater   | Asymptotic : 0.6122, Inf
      Greater   |      Exact : 0.6121, Inf
  
  
  Title:
   Mood Two-Sample Test of Scale
  
  Test Results:
    STATISTIC:
      Z: -1.4862
    P VALUE:
      Alternative Two-Sided: 0.1372 
      Alternative      Less: 0.06861 
      Alternative   Greater: 0.9314 
  
   done successfully.
  
  
  
  Executing test function test.varianceTests  ... 
  Title:
   F Test of Variances
  
  Test Results:
    PARAMETER:
      Hypothesized Ratio: 1
      Numerator   df: 99
      Denumerator df: 49
    SAMPLE ESTIMATES:
      Ratio of Variances: 0.421
    STATISTIC:
      F: 0.421
    P VALUE:
      Alternative Two-Sided: 0.0002723 
      Alternative      Less: 0.0001361 
      Alternative   Greater: 0.9999 
    CONFIDENCE INTERVAL:
      Two-Sided: 0.253, 0.6725
           Less: 0, 0.6238
        Greater: 0.275, Inf
  
  
  Title:
   Bartlett Test for Homogeneity of Variances
  
  Test Results:
    STATISTIC:
      Bartlett's Chi-squared: 13.0406
    P VALUE:
      0.0003048 
  
  
  Title:
   Fligner-Killeen Test for Homogeneity of Variances
  
  Test Results:
    STATISTIC:
      FK:med chi-squared: 2.434
    P VALUE:
      0.1187 
  
   done successfully.
  
  
  
  Executing test function test.akimaInterp  ...  done successfully.
  
  
  
  Executing test function test.akimaInterpp  ...  done successfully.
  
  
  
  Executing test function test.as.matrix.ts  ...  done successfully.
  
  
  
  Executing test function test.as.align.default  ...  done successfully.
  
  
  
  Executing test function test.colnames.default  ...  done successfully.
  
  
  
  Executing test function test.rownames.default  ...  done successfully.
  
  
  
  Executing test function test.characterTable  ... Timing stopped at: 0.037 0.001 0.182
  Error in text.default(j, 35 - i, eval(parse(text = paste("\"\\", v[k],  : 
    conversion failure from UTF-8 to latin1 on 'invalid input' in 'mbcsToSbcs'
  In addition: There were 50 or more warnings (use warnings() to see the first 50)
   done successfully.
  
  
  
  Executing test function test.colStats  ...  done successfully.
  
  
  
  Executing test function test.colorLocator  ...  done successfully.
  
  
  
  Executing test function test.greyPalette  ...  done successfully.
  
  
  
  Executing test function test.colorTable  ...  done successfully.
  
  
  
  Executing test function test.decor  ...  done successfully.
  
  
  
  Executing test function test.description  ...  done successfully.
  
  
  
  Executing test function test.distCheck  ...  done successfully.
  
  
  
  Executing test function test.fHTEST  ...  done successfully.
  
  
  
  Executing test function test.isS4  ...  done successfully.
  
  
  
  Executing test function test.gridVector  ...  done successfully.
  
  
  
  Executing test function test.interactivePlot  ...  done successfully.
  
  
  
  Executing test function test.fjulian  ...  done successfully.
  
  
  
  Executing test function test.krigeInterp  ...  done successfully.
  
  
  
  Executing test function test.kurtosis.POSIXct  ...  done successfully.
  
  
  
  Executing test function test.kurtosis.POSIXlt  ...  done successfully.
  
  
  
  Executing test function test.kurtosis.data.frame  ...  done successfully.
  
  
  
  Executing test function test.kurtosis.default  ...  done successfully.
  
  
  
  Executing test function test.portableInnovations  ...  done successfully.
  
  
  
  Executing test function test.randomNumbers  ...  done successfully.
  
  
  
  Executing test function test.linearInterp  ...  done successfully.
  
  
  
  Executing test function test.listDescription  ... 
   stats Description:
  
    Package:            stats
    Version:            4.4.0
    Priority:           base
    Title:              The R Stats Package
    Author:             R Core Team and contributors worldwide
    Maintainer:         R Core Team <do-use-Contact-address@r-project.org>
    Contact:            R-help mailing list <r-help@r-project.org>
    Description:        R statistical functions.
    License:            Part of R 4.4.0
    Imports:            utils, grDevices, graphics
    Suggests:           MASS, Matrix, SuppDists, methods, stats4
    NeedsCompilation:   yes
    Encoding:           UTF-8
    Built:              R 4.4.0; x86_64-pc-linux-gnu; 2023-10-07 07:35:12
                          UTC; unix
  NULL
   done successfully.
  
  
  
  Executing test function test.countFunctions  ... fUtilities 
           0 
   done successfully.
  
  
  
  Executing test function test.listFunctions  ... character(0)
   done successfully.
  
  
  
  Executing test function test.listIndex  ... 
   fBasics Index:
  
    DistributionFits        Parametric fit of a distribution
    Heaviside               Heaviside and related functions
    Ids                     Set and retrieve column/row names
    NormalityTests          Tests for normality
    acfPlot                 Autocorrelation function plots
    akimaInterp             Bivariate Spline Interpolation
    baseMethods             Generic functions extensions
    basicStats              Basic time series statistics
    boxPlot                 Time series box plots
    characterTable          Table of characters
    colVec                  Column and row vectors
    colorLocator            Color selection
    colorPalette            Color palettes
    colorTable              Table of colors
    correlationTest         Correlation tests
    decor                   Functions for decorating plots
    dght                    Generalized Hyperbolic Student-t
    distCheck               Distribution check
    fBasics-deprecated      Deprecated functions in package fBasics
    fBasics-package         Portfolio modelling, optimization and
                            backtesting
    fBasicsData             fBasics data sets
    fDISTFIT-class          Class '"fDISTFIT"'
    fHTEST-class            Class '"fHTEST"'
    getS4                   General S4 Class Extractor Functions
    gh                      Generalized Hyperbolic Distribution
    ghFit                   GH Distribution Fit
    ghMode                  Generalized Hyperbolic Mode
    ghMoments               Generalized Hyperbolic Distribution Moments
    ghRobMoments            Robust Moments for the GH
    ghSlider                Generalized Hyperbolic Distribution Slider
    ghtFit                  GHT distribution fit
    ghtMode                 Generalized Hyperbolic Student-t Mode
    ghtMoments              Generalized Hyperbolic Student-t Moments
    ghtRobMoments           Robust Moments for the GHT
    gld                     Generalized Lambda Distribution
    gldFit                  GH Distribution Fit
    gldMode                 Generalized Lambda Distribution Mode
    gldRobMoments           Robust Moments for the GLD
    gridVector              Grid vector coordinates
    hilbert                 Hilbert matrix
    histPlot                Histogram and density plots
    hyp                     Hyperbolic distribution
    hypFit                  Fit a Hyperbolic distribution
    hypMode                 Hyperbolic mode
    hypMoments              Hyperbolic distribution moments
    hypRobMoments           Robust moments for the HYP
    hypSlider               Hyperbolic distribution slider
    interactivePlot         Interactive Plot Utility
    inv                     The inverse of a matrix
    krigeInterp             Bivariate Krige Interpolation
    kron                    Kronecker product
    ks2Test                 Two sample Kolmogorov-Smirnov test
    lcg                     Generator for Portable random innovations
    linearInterp            Bivariate Linear Interpolation
    listFunctions           List exported functions in a package
    locationTest            Two sample location tests
    maxdd                   Drawdown statistics
    nig                     Normal Inverse Gaussian Distribution
    nigFit                  Fit of a Normal Inverse Gaussian Distribution
    nigMode                 Normal Inverse Gaussian Mode
    nigMoments              Moments for the Normal Inverse Gaussian
    nigRobMoments           Robust Moments for the NIG
    nigShapeTriangle        NIG Shape Triangle
    nigSlider               nigerbolic Distribution Slider
    norm2                   Matrix norm
    normRobMoments          Robust moments for the Normal distribution
    pascal                  Pascal matrix
    pdl                     Polynomial distributed lags
    positiveDefinite        Positive definite matrices
    print.control           Print control
    qqnormPlot              Quantile-Quantile plots
    returnSeriesGUI         Return series plots
    rk                      The rank of a matrix
    rowStats                Row statistics
    sampleLMoments          Sample L-moments
    sampleRobMoments        Robust moments for the GLD
    scaleTest               Two sample scale tests
    scalinglawPlot          Scaling law behaviour
    seriesPlot              Financial time series plots
    sgh                     Standardized Generalized Hyperbolic
                            Distribution
    sghFit                  Standardized GH distribution fit
    sght                    Standardized generalized hyperbolic Student-t
                            Distribution
    snig                    Standardized Normal Inverse Gaussian
                            Distribution
    snigFit                 Fit of a Standardized NIG Distribution
    ssd                     Spline Smoothed Distribution
    ssdFit                  Fit density using smoothing splines
    stableSlider            Slider GUI for Stable Distribution
    symbolTable             Table of symbols
    tr                      Trace of a matrix
    triang                  Upper and lower triangular matrices
    tsHessian               Two sided approximated Hessian
    tslag                   Lagged or leading vector/matrix
    varianceTest            Two sample variance tests
    vec                     Stacking vectors and matrices
  NULL
   done successfully.
  
  
  
  Executing test function test.apply  ...  done successfully.
  
  
  
  Executing test function test.creation  ...  done successfully.
  
  
  
  Executing test function test.linearAlgebra  ...  done successfully.
  
  
  
  Executing test function test.mathOps  ...  done successfully.
  
  
  
  Executing test function test.moreOperations  ...  done successfully.
  
  
  
  Executing test function test.subsets  ...  done successfully.
  
  
  
  Executing test function test.plot  ...  done successfully.
  
  
  
  Executing test function test.print  ...  done successfully.
  
  
  
  Executing test function test.hexCode  ...  done successfully.
  
  
  
  Executing test function test.colStats  ...  done successfully.
  
  
  
  Executing test function test.skewness.POSIXct  ...  done successfully.
  
  
  
  Executing test function test.skewness.POSIXlt  ...  done successfully.
  
  
  
  Executing test function test.skewness.data.frame  ...  done successfully.
  
  
  
  Executing test function test.skewness.default  ...  done successfully.
  
  
  
  Executing test function test.sliderMenu  ...  done successfully.
  
  
  
  Executing test function test.subplot  ...  done successfully.
  
  
  
  Executing test function test.subplot  ...  done successfully.
  
  
  
  Executing test function test.symbolTable  ...  done successfully.
  
  
  
  Executing test function test.unitrootNA  ...  done successfully.
  
  RUNIT TEST PROTOCOL -- Sat Oct  7 11:28:04 2023 
  *********************************************** 
  Number of test functions: 87 
  Number of errors: 1 
  Number of failures: 0 
  
   
  1 Test Suite : 
  fBasics unit testing - 87 test functions, 1 error, 0 failures
  ERROR in test.characterTable: Error in text.default(j, 35 - i, eval(parse(text = paste("\"\\", v[k],  : 
    conversion failure from UTF-8 to latin1 on 'invalid input' in 'mbcsToSbcs'
  Error in eval(ei, envir) : 
  
  unit testing failed (#test failures: 0, R errors: 1)
  
  Calls: source -> withVisible -> eval -> eval
  In addition: There were 50 or more warnings (use warnings() to see the first 50)
  Execution halted