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/dports/devel/hyperscan/boost_1_75_0/libs/mpl/doc/src/refmanual/
H A Dset_c.rst68 typedef set_c< int,1,3,5,7,9 > odds;
70 BOOST_MPL_ASSERT_RELATION( size<odds>::value, ==, 5 );
71 BOOST_MPL_ASSERT_NOT(( empty<odds> ));
73 BOOST_MPL_ASSERT(( has_key< odds, integral_c<int,5> > ));
74 BOOST_MPL_ASSERT_NOT(( has_key< odds, integral_c<int,4> > ));
75 BOOST_MPL_ASSERT_NOT(( has_key< odds, integral_c<int,15> > ));
/dports/science/py-scipy/scipy-1.7.1/scipy/stats/
H A Dbiasedurn.pyx.templ32 def __cinit__(self, int n, int m, int N, double odds, double accuracy):
33 …_fnch = unique_ptr[CFishersNCHypergeometric](new CFishersNCHypergeometric(n, m, N, odds, accuracy))
56 def __cinit__(self, int n, int m, int N, double odds, double accuracy):
152 def rvs_fisher(self, int n, int m, int N, double odds, int size, random_state=None):
159 rvs[ii] = self.c_sl3.get().FishersNCHyp(n, m, N, odds)
162 def rvs_wallenius(self, int n, int m, int N, double odds, int size, random_state=None):
169 rvs[ii] = self.c_sl3.get().WalleniusNCHyp(n, m, N, odds)
172 def FishersNCHyp(self, int n, int m, int N, double odds):
174 return self.c_sl3.get().FishersNCHyp(n, m, N, odds)
176 def WalleniusNCHyp(self, int n, int m, int N, double odds):
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/dports/multimedia/scte35dump/scte35dump-0.1.6/cargo-crates/odds-0.2.26/
H A DCargo.toml.orig-cargo2 name = "odds"
7 …s for strings and vectors: `repeat`, `insert_str` and `splice`. Things in odds may move to more ap…
8 documentation = "https://docs.rs/odds/"
9 repository = "https://github.com/bluss/odds"
H A DREADME.rst2 odds chapter
10 __ https://docs.rs/odds/
14 .. |build_status| image:: https://travis-ci.org/bluss/odds.svg
15 .. _build_status: https://travis-ci.org/bluss/odds
17 .. |crates| image:: http://meritbadge.herokuapp.com/odds
18 .. _crates: https://crates.io/crates/odds
100 - Add default feature "std". odds uses ``no_std`` if you opt out of this
137 - Add `odds::string::StrExt`, extensions to `&str`.
/dports/devel/R-cran-vcd/vcd/man/
H A Dloddsratio.Rd23 Computes (log) odds ratios and their asymptotic variance covariance
61 odds ratios. By default, odds ratios for profile contrasts (or sequential
77 be applied before computing odds ratios?
95 For an R x C table, (log) odds ratios are formed for the set of (R-1) x (C-1)
103 These are sometimes called \dQuote{local odds ratios}.
115 other possible odds ratios from any non-redundant set, but the interpretation
128 containing the log odds ratios. Use the \code{coef} method to
134 \item{vcov}{Variance covariance matrix of the log odds ratios.}
165 log odds ratios and their asymptotic covariance matrix.
174 (or for odds ratios, with \code{log = FALSE}).
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/dports/lang/ghc/ghc-8.10.7/libraries/containers/containers-tests/benchmarks/LookupGE/
H A DMap.hs23 elems_odd = zip odds odds
26 odds = [1,3..bound] function
31 , \(n,fun) -> bench (n++" far") $ nf (fge fun odds) m_large
34 , \(n,fun) -> bench (n++" !far") $ nf (fge2 fun odds) m_large
H A DIntMap.hs23 elems_odd = zip odds odds
26 odds = [1,3..bound] function
31 , \(n,fun) -> bench (n++" far") $ nf (fge fun odds) m_large
34 , \(n,fun) -> bench (n++" !far") $ nf (fge2 fun odds) m_large
/dports/lang/elm/compiler-0.19.1/_cabal_deps/containers-0.5.11.0/benchmarks/LookupGE/
H A DIntMap.hs23 elems_odd = zip odds odds
26 odds = [1,3..bound] function
31 , \(n,fun) -> bench (n++" far") $ nf (fge fun odds) m_large
34 , \(n,fun) -> bench (n++" !far") $ nf (fge2 fun odds) m_large
H A DMap.hs23 elems_odd = zip odds odds
26 odds = [1,3..bound] function
31 , \(n,fun) -> bench (n++" far") $ nf (fge fun odds) m_large
34 , \(n,fun) -> bench (n++" !far") $ nf (fge2 fun odds) m_large
/dports/devel/boost-docs/boost_1_72_0/libs/hana/example/ext/std/array/
H A Dorderable.cpp13 constexpr std::array<int, 4> odds = {{1, 3, 5, 7}}; variable
18 static_assert(hana::less(odds, evens), "");
21 static_assert(hana::less(up_to_5, odds), "");
/dports/devel/boost-python-libs/boost_1_72_0/libs/hana/example/ext/std/array/
H A Dorderable.cpp13 constexpr std::array<int, 4> odds = {{1, 3, 5, 7}}; variable
18 static_assert(hana::less(odds, evens), "");
21 static_assert(hana::less(up_to_5, odds), "");
/dports/devel/boost-libs/boost_1_72_0/libs/hana/example/ext/std/array/
H A Dorderable.cpp13 constexpr std::array<int, 4> odds = {{1, 3, 5, 7}}; variable
18 static_assert(hana::less(odds, evens), "");
21 static_assert(hana::less(up_to_5, odds), "");
/dports/devel/hyperscan/boost_1_75_0/libs/hana/example/ext/std/array/
H A Dorderable.cpp13 constexpr std::array<int, 4> odds = {{1, 3, 5, 7}}; variable
18 static_assert(hana::less(odds, evens), "");
21 static_assert(hana::less(up_to_5, odds), "");
/dports/math/symphony/SYMPHONY-releases-5.6.17/SYMPHONY/Applications/MPP/src/CutGen/
H A Dmpp_cg.c74 int *odds; in user_find_cuts() local
88 odds = (int *) calloc(mpp->numnodes, sizeof(int)); in user_find_cuts()
152 odds[current_component]++; in user_find_cuts()
166 odds[current_component]++; in user_find_cuts()
187 if (odds[i]%2 == 1 && cut_sizes[i] > 1){ in user_find_cuts()
214 FREE(odds); in user_find_cuts()
/dports/devel/R-cran-Hmisc/Hmisc/R/
H A Dpopower.s1 popower <- function(p, odds.ratio, n, n1, n2, alpha=.05)
17 power <- pnorm(abs(logb(odds.ratio))*sqrt(V) - z)
32 posamsize <- function(p, odds.ratio, fraction=.5,
40 log.or <- logb(odds.ratio)
/dports/games/wolfpack/empire-4.4.1/src/lib/commands/
H A Dsabo.c46 double odds; in c_sabotage() local
74 odds = LND_SPY_DETECT_CHANCE(land.lnd_effic); in c_sabotage()
75 if (chance(odds)) { in c_sabotage()
107 if (chance(odds)) { in c_sabotage()
/dports/textproc/sonic/sonic-1.3.0/cargo-crates/librocksdb-sys-6.7.4/rocksdb/test_util/
H A Dsync_point_impl.cc11 void TestKillRandom(std::string kill_point, int odds, in TestKillRandom() argument
19 assert(odds > 0); in TestKillRandom()
20 if (odds % 7 == 0) { in TestKillRandom()
23 odds++; in TestKillRandom()
26 bool crash = r->OneIn(odds); in TestKillRandom()
/dports/databases/mariadb104-server/mariadb-10.4.24/storage/rocksdb/rocksdb/test_util/
H A Dsync_point_impl.cc11 void TestKillRandom(std::string kill_point, int odds, in TestKillRandom() argument
19 assert(odds > 0); in TestKillRandom()
20 if (odds % 7 == 0) { in TestKillRandom()
23 odds++; in TestKillRandom()
26 bool crash = r->OneIn(odds); in TestKillRandom()
/dports/databases/mariadb104-client/mariadb-10.4.24/storage/rocksdb/rocksdb/test_util/
H A Dsync_point_impl.cc11 void TestKillRandom(std::string kill_point, int odds,
19 assert(odds > 0);
20 if (odds % 7 == 0) {
23 odds++;
26 bool crash = r->OneIn(odds);
/dports/databases/mariadb103-client/mariadb-10.3.34/storage/rocksdb/rocksdb/test_util/
H A Dsync_point_impl.cc11 void TestKillRandom(std::string kill_point, int odds, in TestKillRandom() argument
19 assert(odds > 0); in TestKillRandom()
20 if (odds % 7 == 0) { in TestKillRandom()
23 odds++; in TestKillRandom()
26 bool crash = r->OneIn(odds); in TestKillRandom()
/dports/databases/mariadb103-server/mariadb-10.3.34/storage/rocksdb/rocksdb/test_util/
H A Dsync_point_impl.cc11 void TestKillRandom(std::string kill_point, int odds, in TestKillRandom() argument
19 assert(odds > 0); in TestKillRandom()
20 if (odds % 7 == 0) { in TestKillRandom()
23 odds++; in TestKillRandom()
26 bool crash = r->OneIn(odds); in TestKillRandom()
/dports/databases/mariadb105-client/mariadb-10.5.15/storage/rocksdb/rocksdb/test_util/
H A Dsync_point_impl.cc11 void TestKillRandom(std::string kill_point, int odds, in TestKillRandom() argument
19 assert(odds > 0); in TestKillRandom()
20 if (odds % 7 == 0) { in TestKillRandom()
23 odds++; in TestKillRandom()
26 bool crash = r->OneIn(odds); in TestKillRandom()
/dports/databases/mariadb105-server/mariadb-10.5.15/storage/rocksdb/rocksdb/test_util/
H A Dsync_point_impl.cc11 void TestKillRandom(std::string kill_point, int odds, in TestKillRandom() argument
19 assert(odds > 0); in TestKillRandom()
20 if (odds % 7 == 0) { in TestKillRandom()
23 odds++; in TestKillRandom()
26 bool crash = r->OneIn(odds); in TestKillRandom()
/dports/textproc/p5-Text-NSP/Text-NSP-1.31/lib/Text/NSP/Measures/2D/
H A Dodds.pm61 package Text::NSP::Measures::2D::odds;
120 my $odds = (($n11*$n22) / ($n12*$n21));
122 return ($odds);
/dports/math/R-cran-LearnBayes/LearnBayes/man/
H A Dmnormt.onesided.Rd18 \item{prior.odds}{prior odds of the null hypothesis}
19 \item{post.odds}{posterior odds of the null hypothesis}

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