@@ -948,6 +948,7 @@ def test_beta(self):
948948 Unit ,
949949 {"alpha" : Rplus , "beta" : Rplus },
950950 lambda value , alpha , beta : sp .beta .logcdf (value , alpha , beta ),
951+ n_samples = 10 ,
951952 )
952953
953954 def test_kumaraswamy (self ):
@@ -1052,17 +1053,20 @@ def scipy_mu_alpha_logcdf(value, mu, alpha):
10521053 Nat ,
10531054 {"mu" : Rplus , "alpha" : Rplus },
10541055 scipy_mu_alpha_logcdf ,
1056+ n_samples = 5 ,
10551057 )
10561058 self .check_logcdf (
10571059 NegativeBinomial ,
10581060 Nat ,
10591061 {"p" : Unit , "n" : Rplus },
10601062 lambda value , p , n : sp .nbinom .logcdf (value , n , p ),
1063+ n_samples = 5 ,
10611064 )
10621065 self .check_selfconsistency_discrete_logcdf (
10631066 NegativeBinomial ,
10641067 Nat ,
10651068 {"mu" : Rplus , "alpha" : Rplus },
1069+ n_samples = 10 ,
10661070 )
10671071
10681072 @pytest .mark .parametrize (
@@ -1282,11 +1286,13 @@ def test_binomial(self):
12821286 Nat ,
12831287 {"n" : NatSmall , "p" : Unit },
12841288 lambda value , n , p : sp .binom .logcdf (value , n , p ),
1289+ n_samples = 10 ,
12851290 )
12861291 self .check_selfconsistency_discrete_logcdf (
12871292 Binomial ,
12881293 Nat ,
12891294 {"n" : NatSmall , "p" : Unit },
1295+ n_samples = 10 ,
12901296 )
12911297
12921298 # Too lazy to propagate decimal parameter through the whole chain of deps
@@ -1423,6 +1429,7 @@ def test_zeroinflatednegativebinomial(self):
14231429 ZeroInflatedNegativeBinomial ,
14241430 Nat ,
14251431 {"mu" : Rplusbig , "alpha" : Rplusbig , "psi" : Unit },
1432+ n_samples = 10 ,
14261433 )
14271434
14281435 # Too lazy to propagate decimal parameter through the whole chain of deps
@@ -1437,6 +1444,7 @@ def test_zeroinflatedbinomial(self):
14371444 ZeroInflatedBinomial ,
14381445 Nat ,
14391446 {"n" : NatSmall , "p" : Unit , "psi" : Unit },
1447+ n_samples = 10 ,
14401448 )
14411449
14421450 @pytest .mark .parametrize ("n" , [1 , 2 , 3 ])
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