Open RobinHankin opened 10 months ago
Sometimes it returns a value and sometimes an error is thrown. I hesitate to say "works" because:
samep.test(skating,c("slutskaya","kwan","hughes"))
##
## Constrained support maximization
##
## data: skating
## null hypothesis: slutskaya = kwan = hughes
## null estimate:
## babiakova butyrskaya cohen fontana giunchi gusmeroli
## 3.4434e-06 4.9650e-03 8.6052e-02 3.2119e-04 8.3833e-06 6.4434e-05
## hegel hubert hughes kettunen kopac kwan
## 6.9880e-06 2.2718e-04 2.9328e-01 1.1148e-03 2.2230e-06 2.9328e-01
## liashenko luca maniachenko meier onda robinson
## 4.5101e-04 5.0343e-07 7.4024e-04 2.5567e-04 4.2841e-04 5.0280e-03
## sebestyen slutskaya soldatova suguri volchkova
## 2.4650e-03 2.9328e-01 8.9931e-06 1.7130e-02 8.9147e-04
## (argmax, constrained optimization)
## Support for null: -227.89 + K
##
## alternative hypothesis: sum p_i=1
## alternative estimate:
## babiakova butyrskaya cohen fontana giunchi gusmeroli
## 4.3112e-06 4.8978e-03 8.6031e-02 3.3198e-04 9.1760e-06 7.1191e-05
## hegel hubert hughes kettunen kopac kwan
## 8.2830e-06 2.4259e-04 3.0212e-01 1.2563e-03 2.6104e-06 2.6156e-01
## liashenko luca maniachenko meier onda robinson
## 4.7050e-04 1.0000e-06 7.3469e-04 2.6326e-04 4.4246e-04 4.8840e-03
## sebestyen slutskaya soldatova suguri volchkova
## 2.3920e-03 3.1616e-01 1.0698e-05 1.7073e-02 1.0381e-03
## (argmax, free optimization)
## Support for alternative: -229.22 + K
##
## degrees of freedom: 2
## support difference = -1.3235
## p-value: 1
Above we see an impossible situation in which the constrained likelihood is higher than the unconstrained likelihood.
It's possible to ameliorate the problem a tiny bit by using the (null) evaluate as a starting point:
library("hyper2")
#> Loading required package: cubature
samep.test(skating, c("slutskaya","kwan","hughes"),startp=skating_maxp)
#>
#> Constrained support maximization
#>
#> data: skating
#> null hypothesis: slutskaya = kwan = hughes
#> null estimate:
#> babiakova butyrskaya cohen fontana giunchi gusmeroli
#> 5.047230e-06 5.304464e-03 9.024140e-02 3.683279e-04 1.137324e-05 8.316906e-05
#> hegel hubert hughes kettunen kopac kwan
#> 9.785622e-06 2.689828e-04 2.909049e-01 1.376411e-03 2.996664e-06 2.909049e-01
#> liashenko luca maniachenko meier onda robinson
#> 5.188620e-04 1.000001e-06 8.068784e-04 2.928086e-04 4.880185e-04 5.308256e-03
#> sebestyen slutskaya soldatova suguri volchkova
#> 2.588300e-03 2.909049e-01 1.269274e-05 1.845713e-02 1.139378e-03
#> (argmax, constrained optimization)
#> Support for null: -229.341 + K
#>
#> alternative hypothesis: sum p_i=1
#> alternative estimate:
#> babiakova butyrskaya cohen fontana giunchi gusmeroli
#> 5.047235e-06 5.304470e-03 9.024149e-02 3.683282e-04 1.137326e-05 8.316914e-05
#> hegel hubert hughes kettunen kopac kwan
#> 9.785631e-06 2.689831e-04 2.983166e-01 1.376412e-03 2.996667e-06 2.655059e-01
#> liashenko luca maniachenko meier onda robinson
#> 5.188626e-04 1.000000e-06 8.068792e-04 2.928089e-04 4.880190e-04 5.308262e-03
#> sebestyen slutskaya soldatova suguri volchkova
#> 2.588302e-03 3.088930e-01 1.269275e-05 1.845715e-02 1.138379e-03
#> (argmax, free optimization)
#> Support for alternative: -229.2836 + K
#>
#> degrees of freedom: 2
#> support difference = 0.05737755
#> p-value: 0.9442375
Created on 2024-03-07 with reprex v2.1.0
We see that the unconstrained optimization is unable to find a better estimate, but at least it's not worse.
reproducible, and not the same thing as the "wmmin not finite" bug: