Rat (Release Audit Tool) resultsThe following document contains the results of Rat (Release Audit Tool). ***************************************************** Summary ------- Generated at: 2024-04-05T11:38:31+02:00 Notes: 3 Binaries: 4 Archives: 0 Standards: 1059 Apache Licensed: 1046 Generated Documents: 0 JavaDocs are generated, thus a license header is optional. 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AL /home/gilles/gilles/devel/java/apache/commons-math/trunk/commons-math-legacy/src/main/java/org/apache/commons/math4/legacy/stat/correlation/StorelessCovariance.java !????? /home/gilles/gilles/devel/java/apache/commons-math/trunk/commons-math-legacy/src/main/resources/assets/org/apache/commons/math4/legacy/random/new-joe-kuo-6.21201 AL /home/gilles/gilles/devel/java/apache/commons-math/trunk/commons-math-legacy/pom.xml N /home/gilles/gilles/devel/java/apache/commons-math/trunk/commons-math-legacy/NOTICE ***************************************************** Printing headers for text files without a valid license header... ===================================================== == File: /home/gilles/gilles/devel/java/apache/commons-math/trunk/commons-math-legacy/src/test/resources/org/apache/commons/math4/legacy/distribution/testData.txt ===================================================== 4.038625496201205 3.6485326248346936 3.6651209675932845 5.814896279561131 5.384126469824717 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/home/gilles/gilles/devel/java/apache/commons-math/trunk/commons-math-legacy/src/test/resources/org/apache/commons/math4/legacy/random/emptyFile.txt ===================================================== ===================================================== == File: /home/gilles/gilles/devel/java/apache/commons-math/trunk/commons-math-legacy/src/test/resources/org/apache/commons/math4/legacy/stat/data/NumAcc1.txt ===================================================== File Name: NumAcc1.dat File Format: ASCII Header : lines 1 to 60 (= 60) Certified Values: lines 41 to 43 (= 3) Data : lines 61 to 63 (= 3) Dataset Name: NumAcc1 Description: This is a constructed/fabricated data set to test accuracy in summary statistic calculations. The numbers are large (8-digit integers) and differ only in the last decimal place. Note--by construction, this data set has sample mean = 10000002 (exact) sample standard deviation = 1 (exact) sample autocorrelation coef. = -0.5 (exact) Stat Category: Univariate: Summary Statistics Reference: Simon, Stephen D. and Lesage, James P. (1989). Assessing the Accuracy of ANOVA Caluclations in Statistical Software", Computational Statistics & data Analysis, 8, pp. 325-332. Data: Constructed 1 Response : y 0 Predictors 3 Observations Model: Lower Level of Difficulty 2 Parameters : mu, sigma 1 Response Variable : y 0 Predictor Variables y = mu + e Certified Values Sample Mean ybar: 10000002 Sample Standard Deviation (denom. = n-1) s: 1 Sample Autocorrelation Coefficient (lag 1) r(1): -0.5 Number of Observations: 3 ===================================================== == File: /home/gilles/gilles/devel/java/apache/commons-math/trunk/commons-math-legacy/src/test/resources/org/apache/commons/math4/legacy/stat/data/Michelso.txt ===================================================== File Name: Michelso.dat File Format: ASCII Header : lines 1 to 60 (= 60) Certified Values: lines 41 to 43 (= 3) Data : lines 61 to 160 (= 100) Dataset Name: Michelso (Speed of Light Data, in millions of meters per second) Description: This is an observed/"real world" data set consisting of 100 measurements of the speed of light in air. This classic experiment was carried out by Michelson is 1879. We here use this data to test accuracy in summary statistics calculations. Stat Category: Univariate: Summary Statistics Reference: Dorsey, Ernest N. (1944). The Velocity of Light. Transactions of the American Philiosophical Society, Volume 34, Part 1, Pages 1-110, Table 22. y = mu + e Certified Values Sample Mean ybar: 299.852400000000 Sample Standard Deviation (denom. = n-1) s: 0.0790105478190518 Sample Autocorrelation Coefficient (lag 1) r(1): 0.535199668621283 Number of Observations: 100 ===================================================== == File: /home/gilles/gilles/devel/java/apache/commons-math/trunk/commons-math-legacy/src/test/resources/org/apache/commons/math4/legacy/stat/data/NumAcc2.txt ===================================================== File Name: NumAcc2.dat File Format: ASCII Header : lines 1 to 60 (= 60) Certified Values: lines 41 to 43 (= 3) Data : lines 61 to 1061 (= 1001) Dataset Name: NumAcc2 Description: This is a constructed/fabricated data set to test accuracy in summary statistic calculations. The numbers are 2-digit floating point values and differ only in the last decimal place. Note--by construction, this data set has sample mean = 1.2 (exact) sample standard deviation = 0.1 (exact) sample autocorrelation coef. = -0.999 (exact) Stat Category: Univariate Reference: Simon, Stephen D. and Lesage, James P. (1989). Assessing the Accuracy of ANOVA Caluclations in Statistical Software", Computational Statistics & data Analysis, 8, pp. 325-332. Data: Constructed 1 Response : y 0 Predictors 1001 Observations Model: Average Level of Difficulty 2 Parameters : mu, sigma 1 Response Variable : y 0 Predictor Variables y = mu + e Certified Values Sample Mean ybar: 1.2 Sample Standard Deviation (denom. = n-1) s: 0.1 Sample Autocorrelation Coefficient (lag 1) r(1): -0.999 Number of Observations: 1001 ===================================================== == File: /home/gilles/gilles/devel/java/apache/commons-math/trunk/commons-math-legacy/src/test/resources/org/apache/commons/math4/legacy/stat/data/NumAcc3.txt ===================================================== File Name: NumAcc3.dat File Format: ASCII Header : lines 1 to 60 (= 60) Certified Values: lines 41 to 43 (= 3) Data : lines 61 to 1061 (= 1001) Dataset Name: NumAcc3 Description: This is a constructed/fabricated data set to test accuracy in summary statistic calculations. The numbers are 8-digit floating point values and differ only in the last decimal place. Note--by construction, this data set has sample mean = 1000000.2 (exact) sample standard dev. = 0.1 (exact) sample autocorr. coef. = -0.999 (exact) Stat Category: Univariate: Summary Statistics Reference: Simon, Stephen D. and Lesage, James P. (1989). Assessing the Accuracy of ANOVA Caluclations in Statistical Software", Computational Statistics & data Analysis, 8, pp. 325-332. Data: Constructed 1 Response : y 0 Predictors 1001 Observations Model: Average Level of Difficulty 2 Parameters : mu, sigma 1 Response Variable : y 0 Predictor Variables y = mu + e Certified Values Sample Mean ybar: 1000000.2 Sample Standard Deviation (denom. = n-1) s: 0.1 Sample Autocorrelation Coefficient (lag 1) r(1): -0.999 Number of Observations: 1001 ===================================================== == File: /home/gilles/gilles/devel/java/apache/commons-math/trunk/commons-math-legacy/src/test/resources/org/apache/commons/math4/legacy/stat/data/Lottery.txt ===================================================== ##################################################################### # Dataset Name: Lottery # #Description: This is an observed/"real world" data set # consisting of 218 lottery values # from September 3, 1989 to April 14, 1990 (32 weeks). # One 3-digit random number (from 000 to 999) # is drawn per day, 7 days per week for most # weeks, but fewer days per week for some weeks. # We here use this data to test accuracy # in summary statistics calculations. # # Stat Category: Univariate: Summary Statistics # # Reference: http://www.itl.nist.gov/div898/strd/univ/lottery.html # # Data: "Real World" # 1 Response : y = 3-digit random number # 0 Predictors # 218 Observations # # Model: Lower Level of Difficulty # 2 Parameters : mu, sigma # 1 Response Variable : y # 0 Predictor Variables# # y = mu + e ##################################################################### ##################################################################### # # Certified Values # ##################################################################### mean = 518.958715596330 standardDeviation = 291.699727470969 autocorrelationCoefficient = -0.120948622967393 n = 218 ##################################################################### # # Data # ##################################################################### 162 671 933 414 788 730 817 ===================================================== == File: /home/gilles/gilles/devel/java/apache/commons-math/trunk/commons-math-legacy/src/test/resources/org/apache/commons/math4/legacy/stat/data/PiDigits.txt ===================================================== File Name: PiDigits.dat File Format: ASCII Header : lines 1 to 60 (= 60) Certified Values: lines 41 to 43 (= 3) Data : lines 61 to 5060 (= 5000) Dataset Name: PiDigits Description: This is a constructed/fabricated data set to test accuracy in summary statistic calculations. The numbers are the first 5000 digits of the mathematical constant pi (= 3.1415926535897932384...). Stat Category: Univariate Reference: Mathematics of Computation. January 1962, page 76. Data: Constructed Variable --> 1 Response : y = pi digits --> 0 Predictors --> 5000 Observations Model: Lower Level of Difficulty --> 2 Parameters : mu, sigma --> 1 Response Variable : y --> 0 Predictor Variables y = mu + e Certified Values Sample Mean ybar: 4.53480000000000 Sample Standard Deviation (denom. = n-1) s: 2.86733906028871 Sample Autocorrelation Coefficient (lag 1) r(1): -0.00355099287237972 Number of Observations: 5000 ===================================================== == File: /home/gilles/gilles/devel/java/apache/commons-math/trunk/commons-math-legacy/src/test/resources/org/apache/commons/math4/legacy/stat/data/Mavro.txt ===================================================== File Name: Mavro.dat File Format: ASCII Header : lines 1 to 60 (= 60) Certified Values: lines 41 to 43 (= 3) Data : lines 61 to 110 (= 50) Dataset Name: Mavro (Filter Transmittance Data) Description: This is an observed/"real world" data set consisting of 50 transmittance measurements (at a sampling rate of 10 observations per second) from a filter with a nominal value of 2. The experimenter was Radu Mavrodineaunu, a member of the chemistry staff at NIST. We here use this data to test accuracy in summary statistics calculations. Stat Category: Univariate: Summary Statistics Reference: None Data: "Real World" 1 Response : y = transmittance 0 Predictors 50 Observations Model: Lower Level of Difficulty 2 Parameters : mu, sigma 1 Response Variable : y 0 Predictor Variables y = mu + e Certified Values Sample Mean ybar: 2.00185600000000 Sample Standard Deviation (denom. = n-1) s: 0.000429123454003053 Sample Autocorrelation Coefficient (lag 1) r(1): 0.937989183438248 Number of Observations: 50 ===================================================== == File: /home/gilles/gilles/devel/java/apache/commons-math/trunk/commons-math-legacy/src/test/resources/org/apache/commons/math4/legacy/stat/data/NumAcc4.txt ===================================================== File Name: NumAcc4.dat File Format: ASCII Header : lines 1 to 60 (= 60) Certified Values: lines 41 to 43 (= 3) Data : lines 61 to 1061 (= 1001) Dataset Name: NumAcc4 Description: This is a constructed/fabricated data set to test accuracy in summary statistic calculations. The numbers are 9-digit floating point values and differ only in the last decimal place. sample mean = 10000000.2 (exact) sample standard dev. = 0.1 (exact) sample autocorr. coef. = -0.999 (exact) Stat Category: Univariate Reference: Simon, Stephen D. and Lesage, James P. (1989). Assessing the Accuracy of ANOVA Caluclations in Statistical Software", Computational Statistics & data Analysis, 8, pp. 325-332. Data: Constructed 1 Response : y 0 Predictors 1001 Observations Model: Higher Level of Difficulty 2 Parameters : mu, sigma 1 Response Variable : y 0 Predictor Variables y = mu + e Certified Values Sample Mean ybar: 10000000.2 Sample Standard Deviation (denom. = n-1) s: 0.1 Sample Autocorrelation Coefficient (lag 1) r(1): -0.999 Number of Observations: 1001 ===================================================== == File: /home/gilles/gilles/devel/java/apache/commons-math/trunk/commons-math-legacy/src/test/resources/org/apache/commons/math4/legacy/stat/data/Lew.txt ===================================================== ##################################################################### # Dataset Name: Lew (Beam Deflection Data) # # Description: This is an observed/"real world" data set # consisting of 200 deflections of a steel-concrete # beam while subjected to periodic pressure. # The experimenter was H. S. Lew of the # Center for Building Technology at NIST. # We here use this data to test accuracy # in summary statistics calculations. # # Stat Category: Univariate: Summary Statistics # # Reference: http://www.itl.nist.gov/div898/strd/univ/lew.html # # Data: "Real World" # 1 Response : y = beam deflection # 0 Predictors # 200 Observations # # Model: Lower Level of Difficulty # 2 Parameters : mu, sigma # 1 Response Variable : y # 0 Predictor Variables # y = mu + e ##################################################################### ##################################################################### # # Certified Values # ##################################################################### n = 200 mean = -177.435000000000 standardDeviation = 277.332168044316 autocorrelationCoefficient = -0.307304800605679 ##################################################################### # # R Generated Values # ##################################################################### variance = 76913.13143 max = 300 min = -579 sum = -35487 ##################################################################### # # Data ===================================================== == File: /home/gilles/gilles/devel/java/apache/commons-math/trunk/commons-math-legacy/src/test/maxima/special/RealFunctionValidation/MANIFEST.txt ===================================================== Main-Class: RealFunctionValidation ===================================================== == File: /home/gilles/gilles/devel/java/apache/commons-math/trunk/commons-math-legacy/src/main/resources/assets/org/apache/commons/math4/legacy/random/new-joe-kuo-6.21201 ===================================================== d s a m_i 2 1 0 1 3 2 1 1 3 4 3 1 1 3 1 5 3 2 1 1 1 6 4 1 1 1 3 3 7 4 4 1 3 5 13 8 5 2 1 1 5 5 17 9 5 4 1 1 5 5 5 10 5 7 1 1 7 11 19 11 5 11 1 1 5 1 1 12 5 13 1 1 1 3 11 13 5 14 1 3 5 5 31 14 6 1 1 3 3 9 7 49 15 6 13 1 1 1 15 21 21 16 6 16 1 3 1 13 27 49 17 6 19 1 1 1 15 7 5 18 6 22 1 3 1 15 13 25 19 6 25 1 1 5 5 19 61 20 7 1 1 3 7 11 23 15 103 21 7 4 1 3 7 13 13 15 69 22 7 7 1 1 3 13 7 35 63 23 7 8 1 3 5 9 1 25 53 24 7 14 1 3 1 13 9 35 107 25 7 19 1 3 1 5 27 61 31 26 7 21 1 1 5 11 19 41 61 27 7 28 1 3 5 3 3 13 69 28 7 31 1 1 7 13 1 19 1 29 7 32 1 3 7 5 13 19 59 30 7 37 1 1 3 9 25 29 41 31 7 41 1 3 5 13 23 1 55 32 7 42 1 3 7 3 13 59 17 33 7 50 1 3 1 3 5 53 69 34 7 55 1 1 5 5 23 33 13 35 7 56 1 1 7 7 1 61 123 36 7 59 1 1 7 9 13 61 49 37 7 62 1 3 3 5 3 55 33 38 8 14 1 3 1 15 31 13 49 245 39 8 21 1 3 5 15 31 59 63 97 40 8 22 1 3 1 11 11 11 77 249 41 8 38 1 3 1 11 27 43 71 9 42 8 47 1 1 7 15 21 11 81 45 43 8 49 1 3 7 3 25 31 65 79 44 8 50 1 3 1 1 19 11 3 205 45 8 52 1 1 5 9 19 21 29 157 46 8 56 1 3 7 11 1 33 89 185 47 8 67 1 3 3 3 15 9 79 71 48 8 70 1 3 7 11 15 39 119 27 49 8 84 1 1 3 1 11 31 97 225 50 8 97 1 1 1 3 23 43 57 177 |