[jira] [Updated] (MATH-228) Feature request for one and two sample Kolmogorov-Smirnov test as well as Lilliefors test
[ https://issues.apache.org/jira/browse/MATH-228?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Gilles updated MATH-228: Fix Version/s: (was: 3.1) It looks like there isn't much interest in this issue. Shouldn't it be resolved, as "Won't fix" or "Later"? > Feature request for one and two sample Kolmogorov-Smirnov test as well as > Lilliefors test > - > > Key: MATH-228 > URL: https://issues.apache.org/jira/browse/MATH-228 > Project: Commons Math > Issue Type: New Feature >Affects Versions: 1.2 > Environment: All >Reporter: Anirban Basu >Priority: Minor > Original Estimate: 336h > Remaining Estimate: 336h > > It would be very helpful to have implementations of one and two sample > [Kolmogorov-Smirnov > test|http://en.wikipedia.org/wiki/Kolmogorov-Smirnov_test] as well as > [Lilliefors test|http://en.wikipedia.org/wiki/Lilliefors_test] with > MATLAB-style results in future versions of Commons Math. > For example, Lilliefors test on sample data: > sampleVector = [0.0033413022337048857, 0.008527692135731013, > -0.004902763950955454, 0.033018433100296396, -0.020495504044139023, > 0.003978726052913162, 0.003847972673931109, 0.009160477945515444, > -0.03437653216639, -0.01164235145079795, 0.017180306607011864, > -0.01818483009998717, -0.010479811709006803, -0.033991339307749, > -0.007057160031600951, -1.2398497120424956E-4, 0.0026913151777877564, > 0.03580425341677764, -0.006404370278251359, 0.007579083257585828, > -0.005912037207256193, 0.01241830354576745, -0.0012524631744377235, > -0.005900927958040758, 0.0028847985848513558, 0.005313417226899042, > 0.018923743379700153, 0.010976836172447269, -0.017847220928846164, > 0.0024067380689056783, -0.011912393656503872, -0.019985462687391875, > 0.017318878212931876, 0.003592873590795409, -0.00332615776078915, > -0.018222673013956525, -0.021591768336351125]; > [h, p] = lillietest(sampleVector) > Warning: P is greater than the largest tabulated value, returning 0.5. > > In lillietest at 166 > h = > 0 > p = > 0.5000 > This uses Lilliefors test for normality. The test returns that h=0, i.e. the > null hypothesis that the data vector obeys Normal distribution. -- This message is automatically generated by JIRA. If you think it was sent incorrectly, please contact your JIRA administrators: https://issues.apache.org/jira/secure/ContactAdministrators!default.jspa For more information on JIRA, see: http://www.atlassian.com/software/jira
[jira] [Updated] (MATH-228) Feature request for one and two sample Kolmogorov-Smirnov test as well as Lilliefors test
[ https://issues.apache.org/jira/browse/MATH-228?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Phil Steitz updated MATH-228: - Fix Version/s: (was: 3.0) 3.1 Moving to 3.1, awaiting patch. > Feature request for one and two sample Kolmogorov-Smirnov test as well as > Lilliefors test > - > > Key: MATH-228 > URL: https://issues.apache.org/jira/browse/MATH-228 > Project: Commons Math > Issue Type: New Feature >Affects Versions: 1.2 > Environment: All >Reporter: Anirban Basu >Priority: Minor > Fix For: 3.1 > > Original Estimate: 336h > Remaining Estimate: 336h > > It would be very helpful to have implementations of one and two sample > [Kolmogorov-Smirnov > test|http://en.wikipedia.org/wiki/Kolmogorov-Smirnov_test] as well as > [Lilliefors test|http://en.wikipedia.org/wiki/Lilliefors_test] with > MATLAB-style results in future versions of Commons Math. > For example, Lilliefors test on sample data: > sampleVector = [0.0033413022337048857, 0.008527692135731013, > -0.004902763950955454, 0.033018433100296396, -0.020495504044139023, > 0.003978726052913162, 0.003847972673931109, 0.009160477945515444, > -0.03437653216639, -0.01164235145079795, 0.017180306607011864, > -0.01818483009998717, -0.010479811709006803, -0.033991339307749, > -0.007057160031600951, -1.2398497120424956E-4, 0.0026913151777877564, > 0.03580425341677764, -0.006404370278251359, 0.007579083257585828, > -0.005912037207256193, 0.01241830354576745, -0.0012524631744377235, > -0.005900927958040758, 0.0028847985848513558, 0.005313417226899042, > 0.018923743379700153, 0.010976836172447269, -0.017847220928846164, > 0.0024067380689056783, -0.011912393656503872, -0.019985462687391875, > 0.017318878212931876, 0.003592873590795409, -0.00332615776078915, > -0.018222673013956525, -0.021591768336351125]; > [h, p] = lillietest(sampleVector) > Warning: P is greater than the largest tabulated value, returning 0.5. > > In lillietest at 166 > h = > 0 > p = > 0.5000 > This uses Lilliefors test for normality. The test returns that h=0, i.e. the > null hypothesis that the data vector obeys Normal distribution. -- This message is automatically generated by JIRA. For more information on JIRA, see: http://www.atlassian.com/software/jira
[jira] Updated: (MATH-228) Feature request for one and two sample Kolmogorov-Smirnov test as well as Lilliefors test
[ https://issues.apache.org/jira/browse/MATH-228?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Phil Steitz updated MATH-228: - Fix Version/s: (was: 2.2) 3.0 Still struggling with the distribution, so moving out to 3.0 > Feature request for one and two sample Kolmogorov-Smirnov test as well as > Lilliefors test > - > > Key: MATH-228 > URL: https://issues.apache.org/jira/browse/MATH-228 > Project: Commons Math > Issue Type: New Feature >Affects Versions: 1.2 > Environment: All >Reporter: Anirban Basu >Priority: Minor > Fix For: 3.0 > > Original Estimate: 336h > Remaining Estimate: 336h > > It would be very helpful to have implementations of one and two sample > [Kolmogorov-Smirnov > test|http://en.wikipedia.org/wiki/Kolmogorov-Smirnov_test] as well as > [Lilliefors test|http://en.wikipedia.org/wiki/Lilliefors_test] with > MATLAB-style results in future versions of Commons Math. > For example, Lilliefors test on sample data: > sampleVector = [0.0033413022337048857, 0.008527692135731013, > -0.004902763950955454, 0.033018433100296396, -0.020495504044139023, > 0.003978726052913162, 0.003847972673931109, 0.009160477945515444, > -0.03437653216639, -0.01164235145079795, 0.017180306607011864, > -0.01818483009998717, -0.010479811709006803, -0.033991339307749, > -0.007057160031600951, -1.2398497120424956E-4, 0.0026913151777877564, > 0.03580425341677764, -0.006404370278251359, 0.007579083257585828, > -0.005912037207256193, 0.01241830354576745, -0.0012524631744377235, > -0.005900927958040758, 0.0028847985848513558, 0.005313417226899042, > 0.018923743379700153, 0.010976836172447269, -0.017847220928846164, > 0.0024067380689056783, -0.011912393656503872, -0.019985462687391875, > 0.017318878212931876, 0.003592873590795409, -0.00332615776078915, > -0.018222673013956525, -0.021591768336351125]; > [h, p] = lillietest(sampleVector) > Warning: P is greater than the largest tabulated value, returning 0.5. > > In lillietest at 166 > h = > 0 > p = > 0.5000 > This uses Lilliefors test for normality. The test returns that h=0, i.e. the > null hypothesis that the data vector obeys Normal distribution. -- This message is automatically generated by JIRA. - You can reply to this email to add a comment to the issue online.
[jira] Updated: (MATH-228) Feature request for one and two sample Kolmogorov-Smirnov test as well as Lilliefors test
[ https://issues.apache.org/jira/browse/MATH-228?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Phil Steitz updated MATH-228: - Fix Version/s: 2.2 (was: 2.1) > Feature request for one and two sample Kolmogorov-Smirnov test as well as > Lilliefors test > - > > Key: MATH-228 > URL: https://issues.apache.org/jira/browse/MATH-228 > Project: Commons Math > Issue Type: New Feature >Affects Versions: 1.2 > Environment: All >Reporter: Anirban Basu >Priority: Minor > Fix For: 2.2 > > Original Estimate: 336h > Remaining Estimate: 336h > > It would be very helpful to have implementations of one and two sample > [Kolmogorov-Smirnov > test|http://en.wikipedia.org/wiki/Kolmogorov-Smirnov_test] as well as > [Lilliefors test|http://en.wikipedia.org/wiki/Lilliefors_test] with > MATLAB-style results in future versions of Commons Math. > For example, Lilliefors test on sample data: > sampleVector = [0.0033413022337048857, 0.008527692135731013, > -0.004902763950955454, 0.033018433100296396, -0.020495504044139023, > 0.003978726052913162, 0.003847972673931109, 0.009160477945515444, > -0.03437653216639, -0.01164235145079795, 0.017180306607011864, > -0.01818483009998717, -0.010479811709006803, -0.033991339307749, > -0.007057160031600951, -1.2398497120424956E-4, 0.0026913151777877564, > 0.03580425341677764, -0.006404370278251359, 0.007579083257585828, > -0.005912037207256193, 0.01241830354576745, -0.0012524631744377235, > -0.005900927958040758, 0.0028847985848513558, 0.005313417226899042, > 0.018923743379700153, 0.010976836172447269, -0.017847220928846164, > 0.0024067380689056783, -0.011912393656503872, -0.019985462687391875, > 0.017318878212931876, 0.003592873590795409, -0.00332615776078915, > -0.018222673013956525, -0.021591768336351125]; > [h, p] = lillietest(sampleVector) > Warning: P is greater than the largest tabulated value, returning 0.5. > > In lillietest at 166 > h = > 0 > p = > 0.5000 > This uses Lilliefors test for normality. The test returns that h=0, i.e. the > null hypothesis that the data vector obeys Normal distribution. -- This message is automatically generated by JIRA. - If you think it was sent incorrectly contact one of the administrators: https://issues.apache.org/jira/secure/Administrators.jspa - For more information on JIRA, see: http://www.atlassian.com/software/jira
[jira] Updated: (MATH-228) Feature request for one and two sample Kolmogorov-Smirnov test as well as Lilliefors test
[ https://issues.apache.org/jira/browse/MATH-228?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Phil Steitz updated MATH-228: - Affects Version/s: (was: 1.3) 1.2 > Feature request for one and two sample Kolmogorov-Smirnov test as well as > Lilliefors test > - > > Key: MATH-228 > URL: https://issues.apache.org/jira/browse/MATH-228 > Project: Commons Math > Issue Type: New Feature >Affects Versions: 1.2 > Environment: All >Reporter: Anirban Basu >Priority: Minor > Fix For: 2.1 > > Original Estimate: 336h > Remaining Estimate: 336h > > It would be very helpful to have implementations of one and two sample > [Kolmogorov-Smirnov > test|http://en.wikipedia.org/wiki/Kolmogorov-Smirnov_test] as well as > [Lilliefors test|http://en.wikipedia.org/wiki/Lilliefors_test] with > MATLAB-style results in future versions of Commons Math. > For example, Lilliefors test on sample data: > sampleVector = [0.0033413022337048857, 0.008527692135731013, > -0.004902763950955454, 0.033018433100296396, -0.020495504044139023, > 0.003978726052913162, 0.003847972673931109, 0.009160477945515444, > -0.03437653216639, -0.01164235145079795, 0.017180306607011864, > -0.01818483009998717, -0.010479811709006803, -0.033991339307749, > -0.007057160031600951, -1.2398497120424956E-4, 0.0026913151777877564, > 0.03580425341677764, -0.006404370278251359, 0.007579083257585828, > -0.005912037207256193, 0.01241830354576745, -0.0012524631744377235, > -0.005900927958040758, 0.0028847985848513558, 0.005313417226899042, > 0.018923743379700153, 0.010976836172447269, -0.017847220928846164, > 0.0024067380689056783, -0.011912393656503872, -0.019985462687391875, > 0.017318878212931876, 0.003592873590795409, -0.00332615776078915, > -0.018222673013956525, -0.021591768336351125]; > [h, p] = lillietest(sampleVector) > Warning: P is greater than the largest tabulated value, returning 0.5. > > In lillietest at 166 > h = > 0 > p = > 0.5000 > This uses Lilliefors test for normality. The test returns that h=0, i.e. the > null hypothesis that the data vector obeys Normal distribution. -- This message is automatically generated by JIRA. - You can reply to this email to add a comment to the issue online.
[jira] Updated: (MATH-228) Feature request for one and two sample Kolmogorov-Smirnov test as well as Lilliefors test
[ https://issues.apache.org/jira/browse/MATH-228?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Phil Steitz updated MATH-228: - Affects Version/s: (was: 2.1) 1.3 Fix Version/s: (was: 2.0) 2.1 > Feature request for one and two sample Kolmogorov-Smirnov test as well as > Lilliefors test > - > > Key: MATH-228 > URL: https://issues.apache.org/jira/browse/MATH-228 > Project: Commons Math > Issue Type: New Feature >Affects Versions: 1.2 > Environment: All >Reporter: Anirban Basu >Priority: Minor > Fix For: 2.1 > > Original Estimate: 336h > Remaining Estimate: 336h > > It would be very helpful to have implementations of one and two sample > [Kolmogorov-Smirnov > test|http://en.wikipedia.org/wiki/Kolmogorov-Smirnov_test] as well as > [Lilliefors test|http://en.wikipedia.org/wiki/Lilliefors_test] with > MATLAB-style results in future versions of Commons Math. > For example, Lilliefors test on sample data: > sampleVector = [0.0033413022337048857, 0.008527692135731013, > -0.004902763950955454, 0.033018433100296396, -0.020495504044139023, > 0.003978726052913162, 0.003847972673931109, 0.009160477945515444, > -0.03437653216639, -0.01164235145079795, 0.017180306607011864, > -0.01818483009998717, -0.010479811709006803, -0.033991339307749, > -0.007057160031600951, -1.2398497120424956E-4, 0.0026913151777877564, > 0.03580425341677764, -0.006404370278251359, 0.007579083257585828, > -0.005912037207256193, 0.01241830354576745, -0.0012524631744377235, > -0.005900927958040758, 0.0028847985848513558, 0.005313417226899042, > 0.018923743379700153, 0.010976836172447269, -0.017847220928846164, > 0.0024067380689056783, -0.011912393656503872, -0.019985462687391875, > 0.017318878212931876, 0.003592873590795409, -0.00332615776078915, > -0.018222673013956525, -0.021591768336351125]; > [h, p] = lillietest(sampleVector) > Warning: P is greater than the largest tabulated value, returning 0.5. > > In lillietest at 166 > h = > 0 > p = > 0.5000 > This uses Lilliefors test for normality. The test returns that h=0, i.e. the > null hypothesis that the data vector obeys Normal distribution. -- This message is automatically generated by JIRA. - You can reply to this email to add a comment to the issue online.
[jira] Updated: (MATH-228) Feature request for one and two sample Kolmogorov-Smirnov test as well as Lilliefors test
[ https://issues.apache.org/jira/browse/MATH-228?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Phil Steitz updated MATH-228: - Affects Version/s: (was: 2.0) 2.1 Moving to 2.1, awaiting patch for this enhancement. > Feature request for one and two sample Kolmogorov-Smirnov test as well as > Lilliefors test > - > > Key: MATH-228 > URL: https://issues.apache.org/jira/browse/MATH-228 > Project: Commons Math > Issue Type: New Feature >Affects Versions: 2.1 > Environment: All >Reporter: Anirban Basu >Priority: Minor > Fix For: 2.0 > > Original Estimate: 336h > Remaining Estimate: 336h > > It would be very helpful to have implementations of one and two sample > [Kolmogorov-Smirnov > test|http://en.wikipedia.org/wiki/Kolmogorov-Smirnov_test] as well as > [Lilliefors test|http://en.wikipedia.org/wiki/Lilliefors_test] with > MATLAB-style results in future versions of Commons Math. > For example, Lilliefors test on sample data: > sampleVector = [0.0033413022337048857, 0.008527692135731013, > -0.004902763950955454, 0.033018433100296396, -0.020495504044139023, > 0.003978726052913162, 0.003847972673931109, 0.009160477945515444, > -0.03437653216639, -0.01164235145079795, 0.017180306607011864, > -0.01818483009998717, -0.010479811709006803, -0.033991339307749, > -0.007057160031600951, -1.2398497120424956E-4, 0.0026913151777877564, > 0.03580425341677764, -0.006404370278251359, 0.007579083257585828, > -0.005912037207256193, 0.01241830354576745, -0.0012524631744377235, > -0.005900927958040758, 0.0028847985848513558, 0.005313417226899042, > 0.018923743379700153, 0.010976836172447269, -0.017847220928846164, > 0.0024067380689056783, -0.011912393656503872, -0.019985462687391875, > 0.017318878212931876, 0.003592873590795409, -0.00332615776078915, > -0.018222673013956525, -0.021591768336351125]; > [h, p] = lillietest(sampleVector) > Warning: P is greater than the largest tabulated value, returning 0.5. > > In lillietest at 166 > h = > 0 > p = > 0.5000 > This uses Lilliefors test for normality. The test returns that h=0, i.e. the > null hypothesis that the data vector obeys Normal distribution. -- This message is automatically generated by JIRA. - You can reply to this email to add a comment to the issue online.
