[rand.dist.bern.negbin]

llvm-svn: 103916

libcxx/include/random

@@ -669,7 +669,62 @@ template<class IntType = int>
     class geometric_distribution;
 
 template<class IntType = int>
-    class negative_binomial_distribution;
+class negative_binomial_distribution
+{
+public:
+    // types
+    typedef IntType result_type;
+
+    class param_type
+    {
+    public:
+        typedef negative_binomial_distribution distribution_type;
+
+        explicit param_type(result_type k = 1, double p = 0.5);
+
+        result_type k() const;
+        double p() const;
+
+        friend bool operator==(const param_type& x, const param_type& y);
+        friend bool operator!=(const param_type& x, const param_type& y);
+    };
+
+    // constructor and reset functions
+    explicit negative_binomial_distribution(result_type k = 1, double p = 0.5);
+    explicit negative_binomial_distribution(const param_type& parm);
+    void reset();
+
+    // generating functions
+    template<class URNG> result_type operator()(URNG& g);
+    template<class URNG> result_type operator()(URNG& g, const param_type& parm);
+
+    // property functions
+    result_type k() const;
+    double p() const;
+
+    param_type param() const;
+    void param(const param_type& parm);
+
+    result_type min() const;
+    result_type max() const;
+
+    friend bool operator==(const negative_binomial_distribution& x,
+                           const negative_binomial_distribution& y);
+    friend bool operator!=(const negative_binomial_distribution& x,
+                           const negative_binomial_distribution& y);
+
+    template <class charT, class traits>
+    friend
+    basic_ostream<charT, traits>&
+    operator<<(basic_ostream<charT, traits>& os,
+               const negative_binomial_distribution& x);
+    
+    template <class charT, class traits>
+    friend
+    basic_istream<charT, traits>&
+    operator>>(basic_istream<charT, traits>& is,
+               negative_binomial_distribution& x);
+};
 
 template<class IntType = int>
 class poisson_distribution
@@ -4098,6 +4153,122 @@ operator>>(basic_istream<_CharT, _Traits>& __is,
     return __is;
 }
 
+// negative_binomial_distribution
+
+template<class _IntType = int>
+class negative_binomial_distribution
+{
+public:
+    // types
+    typedef _IntType result_type;
+
+    class param_type
+    {
+        result_type __k_;
+        double __p_;
+    public:
+        typedef negative_binomial_distribution distribution_type;
+
+        explicit param_type(result_type __k = 1, double __p = 0.5)
+            : __k_(__k), __p_(__p) {}
+
+        result_type k() const {return __k_;}
+        double p() const {return __p_;}
+
+        friend bool operator==(const param_type& __x, const param_type& __y)
+            {return __x.__k_ == __y.__k_ && __x.__p_ == __y.__p_;}
+        friend bool operator!=(const param_type& __x, const param_type& __y)
+            {return !(__x == __y);}
+    };
+
+private:
+    param_type __p_;
+
+public:
+    // constructor and reset functions
+    explicit negative_binomial_distribution(result_type __k = 1, double __p = 0.5)
+        : __p_(__k, __p) {}
+    explicit negative_binomial_distribution(const param_type& __p) : __p_(__p) {}
+    void reset() {}
+
+    // generating functions
+    template<class _URNG> result_type operator()(_URNG& __g)
+        {return (*this)(__g, __p_);}
+    template<class _URNG> result_type operator()(_URNG& __g, const param_type& __p);
+
+    // property functions
+    result_type k() const {return __p_.k();}
+    double p() const {return __p_.p();}
+
+    param_type param() const {return __p_;}
+    void param(const param_type& __p) {__p_ = __p;}
+
+    result_type min() const {return 0;}
+    result_type max() const {return numeric_limits<result_type>::max();}
+
+    friend bool operator==(const negative_binomial_distribution& __x,
+                           const negative_binomial_distribution& __y)
+        {return __x.__p_ == __y.__p_;}
+    friend bool operator!=(const negative_binomial_distribution& __x,
+                           const negative_binomial_distribution& __y)
+        {return !(__x == __y);}
+};
+
+template <class _IntType>
+template<class _URNG>
+_IntType
+negative_binomial_distribution<_IntType>::operator()(_URNG& __urng, const param_type& __pr)
+{
+    result_type __k = __pr.k();
+    double __p = __pr.p();
+    if (__k <= 21 * __p)
+    {
+        bernoulli_distribution __gen(__p);
+        result_type __f = 0;
+        result_type __s = 0;
+        while (__s < __k)
+        {
+            if (__gen(__urng))
+                ++__s;
+            else
+                ++__f;
+        }
+        return __f;
+    }
+    return poisson_distribution<result_type>(gamma_distribution<double>
+                                            (__k, (1-__p)/__p)(__urng))(__urng);
+}
+
+template <class _CharT, class _Traits, class _IntType>
+basic_ostream<_CharT, _Traits>&
+operator<<(basic_ostream<_CharT, _Traits>& __os,
+           const negative_binomial_distribution<_IntType>& __x)
+{
+    __save_flags<_CharT, _Traits> _(__os);
+    __os.flags(ios_base::dec | ios_base::left);
+    _CharT __sp = __os.widen(' ');
+    __os.fill(__sp);
+    return __os << __x.k() << __sp << __x.p();
+}
+
+template <class _CharT, class _Traits, class _IntType>
+basic_istream<_CharT, _Traits>&
+operator>>(basic_istream<_CharT, _Traits>& __is,
+           negative_binomial_distribution<_IntType>& __x)
+{
+    typedef negative_binomial_distribution<_IntType> _Eng;
+    typedef typename _Eng::result_type result_type;
+    typedef typename _Eng::param_type param_type;
+    __save_flags<_CharT, _Traits> _(__is);
+    __is.flags(ios_base::dec | ios_base::skipws);
+    result_type __k;
+    double __p;
+    __is >> __k >> __p;
+    if (!__is.fail())
+        __x.param(param_type(__k, __p));
+    return __is;
+}
+
 // chi_squared_distribution
 
 template<class _RealType = double>

libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bin/eval.pass.cpp

@@ -14,8 +14,6 @@
 
 // template<class _URNG> result_type operator()(_URNG& g);
 
-#include <iostream>
-
 #include <random>
 #include <numeric>
 #include <vector>

libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/assign.pass.cpp

@@ -0,0 +1,34 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class IntType = int>
+// class negative_binomial_distribution
+
+// negative_binomial_distribution& operator=(const negative_binomial_distribution&);
+
+#include <random>
+#include <cassert>
+
+void
+test1()
+{
+    typedef std::negative_binomial_distribution<> D;
+    D d1(2, 0.75);
+    D d2;
+    assert(d1 != d2);
+    d2 = d1;
+    assert(d1 == d2);
+}
+
+int main()
+{
+    test1();
+}

libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/copy.pass.cpp

@@ -0,0 +1,32 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class IntType = int>
+// class negative_binomial_distribution
+
+// negative_binomial_distribution(const negative_binomial_distribution&);
+
+#include <random>
+#include <cassert>
+
+void
+test1()
+{
+    typedef std::negative_binomial_distribution<> D;
+    D d1(2, 0.75);
+    D d2 = d1;
+    assert(d1 == d2);
+}
+
+int main()
+{
+    test1();
+}

libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/ctor_int_double.pass.cpp

@@ -0,0 +1,40 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class IntType = int>
+// class negative_binomial_distribution
+
+// explicit negative_binomial_distribution(IntType t = 1, double p = 0.5);
+
+#include <random>
+#include <cassert>
+
+int main()
+{
+    {
+        typedef std::negative_binomial_distribution<> D;
+        D d;
+        assert(d.k() == 1);
+        assert(d.p() == 0.5);
+    }
+    {
+        typedef std::negative_binomial_distribution<> D;
+        D d(3);
+        assert(d.k() == 3);
+        assert(d.p() == 0.5);
+    }
+    {
+        typedef std::negative_binomial_distribution<> D;
+        D d(3, 0.75);
+        assert(d.k() == 3);
+        assert(d.p() == 0.75);
+    }
+}

libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/ctor_param.pass.cpp

@@ -0,0 +1,30 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class IntType = int>
+// class negative_binomial_distribution
+
+// explicit negative_binomial_distribution(const param_type& parm);
+
+#include <random>
+#include <cassert>
+
+int main()
+{
+    {
+        typedef std::negative_binomial_distribution<> D;
+        typedef D::param_type P;
+        P p(5, 0.25);
+        D d(p);
+        assert(d.k() == 5);
+        assert(d.p() == 0.25);
+    }
+}

libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eq.pass.cpp

@@ -0,0 +1,43 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class IntType = int>
+// class negative_binomial_distribution
+
+// bool operator=(const negative_binomial_distribution& x,
+//                const negative_binomial_distribution& y);
+// bool operator!(const negative_binomial_distribution& x,
+//                const negative_binomial_distribution& y);
+
+#include <random>
+#include <cassert>
+
+int main()
+{
+    {
+        typedef std::negative_binomial_distribution<> D;
+        D d1(3, .25);
+        D d2(3, .25);
+        assert(d1 == d2);
+    }
+    {
+        typedef std::negative_binomial_distribution<> D;
+        D d1(3, .28);
+        D d2(3, .25);
+        assert(d1 != d2);
+    }
+    {
+        typedef std::negative_binomial_distribution<> D;
+        D d1(3, .25);
+        D d2(4, .25);
+        assert(d1 != d2);
+    }
+}

libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eval.pass.cpp

@@ -0,0 +1,270 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class IntType = int>
+// class negative_binomial_distribution
+
+// template<class _URNG> result_type operator()(_URNG& g);
+
+#include <random>
+#include <numeric>
+#include <vector>
+#include <cassert>
+
+template <class T>
+inline
+T
+sqr(T x)
+{
+    return x * x;
+}
+
+int main()
+{
+    {
+        typedef std::negative_binomial_distribution<> D;
+        typedef std::minstd_rand G;
+        G g;
+        D d(5, .25);
+        const int N = 1000000;
+        std::vector<D::result_type> u;
+        for (int i = 0; i < N; ++i)
+        {
+            D::result_type v = d(g);
+            assert(d.min() <= v && v <= d.max());
+            u.push_back(v);
+        }
+        double mean = std::accumulate(u.begin(), u.end(),
+                                              double(0)) / u.size();
+        double var = 0;
+        double skew = 0;
+        double kurtosis = 0;
+        for (int i = 0; i < u.size(); ++i)
+        {
+            double d = (u[i] - mean);
+            double d2 = sqr(d);
+            var += d2;
+            skew += d * d2;
+            kurtosis += d2 * d2;
+        }
+        var /= u.size();
+        double dev = std::sqrt(var);
+        skew /= u.size() * dev * var;
+        kurtosis /= u.size() * var * var;
+        kurtosis -= 3;
+        double x_mean = d.k() * (1 - d.p()) / d.p();
+        double x_var = x_mean / d.p();
+        double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - d.p()));
+        double x_kurtosis = 6. / d.k() + sqr(d.p()) / (d.k() * (1 - d.p()));
+        assert(std::abs(mean - x_mean) / x_mean < 0.01);
+        assert(std::abs(var - x_var) / x_var < 0.01);
+        assert(std::abs(skew - x_skew) / x_skew < 0.01);
+        assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01);
+    }
+    {
+        typedef std::negative_binomial_distribution<> D;
+        typedef std::mt19937 G;
+        G g;
+        D d(30, .03125);
+        const int N = 1000000;
+        std::vector<D::result_type> u;
+        for (int i = 0; i < N; ++i)
+        {
+            D::result_type v = d(g);
+            assert(d.min() <= v && v <= d.max());
+            u.push_back(v);
+        }
+        double mean = std::accumulate(u.begin(), u.end(),
+                                              double(0)) / u.size();
+        double var = 0;
+        double skew = 0;
+        double kurtosis = 0;
+        for (int i = 0; i < u.size(); ++i)
+        {
+            double d = (u[i] - mean);
+            double d2 = sqr(d);
+            var += d2;
+            skew += d * d2;
+            kurtosis += d2 * d2;
+        }
+        var /= u.size();
+        double dev = std::sqrt(var);
+        skew /= u.size() * dev * var;
+        kurtosis /= u.size() * var * var;
+        kurtosis -= 3;
+        double x_mean = d.k() * (1 - d.p()) / d.p();
+        double x_var = x_mean / d.p();
+        double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - d.p()));
+        double x_kurtosis = 6. / d.k() + sqr(d.p()) / (d.k() * (1 - d.p()));
+        assert(std::abs(mean - x_mean) / x_mean < 0.01);
+        assert(std::abs(var - x_var) / x_var < 0.01);
+        assert(std::abs(skew - x_skew) / x_skew < 0.01);
+        assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01);
+    }
+    {
+        typedef std::negative_binomial_distribution<> D;
+        typedef std::mt19937 G;
+        G g;
+        D d(40, .25);
+        const int N = 1000000;
+        std::vector<D::result_type> u;
+        for (int i = 0; i < N; ++i)
+        {
+            D::result_type v = d(g);
+            assert(d.min() <= v && v <= d.max());
+            u.push_back(v);
+        }
+        double mean = std::accumulate(u.begin(), u.end(),
+                                              double(0)) / u.size();
+        double var = 0;
+        double skew = 0;
+        double kurtosis = 0;
+        for (int i = 0; i < u.size(); ++i)
+        {
+            double d = (u[i] - mean);
+            double d2 = sqr(d);
+            var += d2;
+            skew += d * d2;
+            kurtosis += d2 * d2;
+        }
+        var /= u.size();
+        double dev = std::sqrt(var);
+        skew /= u.size() * dev * var;
+        kurtosis /= u.size() * var * var;
+        kurtosis -= 3;
+        double x_mean = d.k() * (1 - d.p()) / d.p();
+        double x_var = x_mean / d.p();
+        double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - d.p()));
+        double x_kurtosis = 6. / d.k() + sqr(d.p()) / (d.k() * (1 - d.p()));
+        assert(std::abs(mean - x_mean) / x_mean < 0.01);
+        assert(std::abs(var - x_var) / x_var < 0.01);
+        assert(std::abs(skew - x_skew) / x_skew < 0.01);
+        assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.03);
+    }
+    {
+        typedef std::negative_binomial_distribution<> D;
+        typedef std::mt19937 G;
+        G g;
+        D d(40, 1);
+        const int N = 1000;
+        std::vector<D::result_type> u;
+        for (int i = 0; i < N; ++i)
+        {
+            D::result_type v = d(g);
+            assert(d.min() <= v && v <= d.max());
+            u.push_back(v);
+        }
+        double mean = std::accumulate(u.begin(), u.end(),
+                                              double(0)) / u.size();
+        double var = 0;
+        double skew = 0;
+        double kurtosis = 0;
+        for (int i = 0; i < u.size(); ++i)
+        {
+            double d = (u[i] - mean);
+            double d2 = sqr(d);
+            var += d2;
+            skew += d * d2;
+            kurtosis += d2 * d2;
+        }
+        var /= u.size();
+        double dev = std::sqrt(var);
+        skew /= u.size() * dev * var;
+        kurtosis /= u.size() * var * var;
+        kurtosis -= 3;
+        double x_mean = d.k() * (1 - d.p()) / d.p();
+        double x_var = x_mean / d.p();
+        double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - d.p()));
+        double x_kurtosis = 6. / d.k() + sqr(d.p()) / (d.k() * (1 - d.p()));
+        assert(mean == x_mean);
+        assert(var == x_var);
+    }
+    {
+        typedef std::negative_binomial_distribution<> D;
+        typedef std::mt19937 G;
+        G g;
+        D d(400, 0.5);
+        const int N = 1000000;
+        std::vector<D::result_type> u;
+        for (int i = 0; i < N; ++i)
+        {
+            D::result_type v = d(g);
+            assert(d.min() <= v && v <= d.max());
+            u.push_back(v);
+        }
+        double mean = std::accumulate(u.begin(), u.end(),
+                                              double(0)) / u.size();
+        double var = 0;
+        double skew = 0;
+        double kurtosis = 0;
+        for (int i = 0; i < u.size(); ++i)
+        {
+            double d = (u[i] - mean);
+            double d2 = sqr(d);
+            var += d2;
+            skew += d * d2;
+            kurtosis += d2 * d2;
+        }
+        var /= u.size();
+        double dev = std::sqrt(var);
+        skew /= u.size() * dev * var;
+        kurtosis /= u.size() * var * var;
+        kurtosis -= 3;
+        double x_mean = d.k() * (1 - d.p()) / d.p();
+        double x_var = x_mean / d.p();
+        double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - d.p()));
+        double x_kurtosis = 6. / d.k() + sqr(d.p()) / (d.k() * (1 - d.p()));
+        assert(std::abs(mean - x_mean) / x_mean < 0.01);
+        assert(std::abs(var - x_var) / x_var < 0.01);
+        assert(std::abs(skew - x_skew) / x_skew < 0.04);
+        assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.05);
+    }
+    {
+        typedef std::negative_binomial_distribution<> D;
+        typedef std::mt19937 G;
+        G g;
+        D d(1, 0.05);
+        const int N = 1000000;
+        std::vector<D::result_type> u;
+        for (int i = 0; i < N; ++i)
+        {
+            D::result_type v = d(g);
+            assert(d.min() <= v && v <= d.max());
+            u.push_back(v);
+        }
+        double mean = std::accumulate(u.begin(), u.end(),
+                                              double(0)) / u.size();
+        double var = 0;
+        double skew = 0;
+        double kurtosis = 0;
+        for (int i = 0; i < u.size(); ++i)
+        {
+            double d = (u[i] - mean);
+            double d2 = sqr(d);
+            var += d2;
+            skew += d * d2;
+            kurtosis += d2 * d2;
+        }
+        var /= u.size();
+        double dev = std::sqrt(var);
+        skew /= u.size() * dev * var;
+        kurtosis /= u.size() * var * var;
+        kurtosis -= 3;
+        double x_mean = d.k() * (1 - d.p()) / d.p();
+        double x_var = x_mean / d.p();
+        double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - d.p()));
+        double x_kurtosis = 6. / d.k() + sqr(d.p()) / (d.k() * (1 - d.p()));
+        assert(std::abs(mean - x_mean) / x_mean < 0.01);
+        assert(std::abs(var - x_var) / x_var < 0.01);
+        assert(std::abs(skew - x_skew) / x_skew < 0.01);
+        assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.02);
+    }
+}

libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eval_param.pass.cpp

@@ -0,0 +1,158 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class IntType = int>
+// class negative_binomial_distribution
+
+// template<class _URNG> result_type operator()(_URNG& g, const param_type& parm);
+
+#include <random>
+#include <numeric>
+#include <vector>
+#include <cassert>
+
+template <class T>
+inline
+T
+sqr(T x)
+{
+    return x * x;
+}
+
+int main()
+{
+    {
+        typedef std::negative_binomial_distribution<> D;
+        typedef D::param_type P;
+        typedef std::minstd_rand G;
+        G g;
+        D d(16, .75);
+        P p(5, .75);
+        const int N = 1000000;
+        std::vector<D::result_type> u;
+        for (int i = 0; i < N; ++i)
+        {
+            D::result_type v = d(g, p);
+            assert(d.min() <= v && v <= d.max());
+            u.push_back(v);
+        }
+        double mean = std::accumulate(u.begin(), u.end(),
+                                              double(0)) / u.size();
+        double var = 0;
+        double skew = 0;
+        double kurtosis = 0;
+        for (int i = 0; i < u.size(); ++i)
+        {
+            double d = (u[i] - mean);
+            double d2 = sqr(d);
+            var += d2;
+            skew += d * d2;
+            kurtosis += d2 * d2;
+        }
+        var /= u.size();
+        double dev = std::sqrt(var);
+        skew /= u.size() * dev * var;
+        kurtosis /= u.size() * var * var;
+        kurtosis -= 3;
+        double x_mean = p.k() * (1 - p.p()) / p.p();
+        double x_var = x_mean / p.p();
+        double x_skew = (2 - p.p()) / std::sqrt(p.k() * (1 - p.p()));
+        double x_kurtosis = 6. / p.k() + sqr(p.p()) / (p.k() * (1 - p.p()));
+        assert(std::abs(mean - x_mean) / x_mean < 0.01);
+        assert(std::abs(var - x_var) / x_var < 0.01);
+        assert(std::abs(skew - x_skew) / x_skew < 0.01);
+        assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01);
+    }
+    {
+        typedef std::negative_binomial_distribution<> D;
+        typedef D::param_type P;
+        typedef std::mt19937 G;
+        G g;
+        D d(16, .75);
+        P p(30, .03125);
+        const int N = 1000000;
+        std::vector<D::result_type> u;
+        for (int i = 0; i < N; ++i)
+        {
+            D::result_type v = d(g, p);
+            assert(d.min() <= v && v <= d.max());
+            u.push_back(v);
+        }
+        double mean = std::accumulate(u.begin(), u.end(),
+                                              double(0)) / u.size();
+        double var = 0;
+        double skew = 0;
+        double kurtosis = 0;
+        for (int i = 0; i < u.size(); ++i)
+        {
+            double d = (u[i] - mean);
+            double d2 = sqr(d);
+            var += d2;
+            skew += d * d2;
+            kurtosis += d2 * d2;
+        }
+        var /= u.size();
+        double dev = std::sqrt(var);
+        skew /= u.size() * dev * var;
+        kurtosis /= u.size() * var * var;
+        kurtosis -= 3;
+        double x_mean = p.k() * (1 - p.p()) / p.p();
+        double x_var = x_mean / p.p();
+        double x_skew = (2 - p.p()) / std::sqrt(p.k() * (1 - p.p()));
+        double x_kurtosis = 6. / p.k() + sqr(p.p()) / (p.k() * (1 - p.p()));
+        assert(std::abs(mean - x_mean) / x_mean < 0.01);
+        assert(std::abs(var - x_var) / x_var < 0.01);
+        assert(std::abs(skew - x_skew) / x_skew < 0.01);
+        assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01);
+    }
+    {
+        typedef std::negative_binomial_distribution<> D;
+        typedef D::param_type P;
+        typedef std::mt19937 G;
+        G g;
+        D d(16, .75);
+        P p(40, .25);
+        const int N = 1000000;
+        std::vector<D::result_type> u;
+        for (int i = 0; i < N; ++i)
+        {
+            D::result_type v = d(g, p);
+            assert(d.min() <= v && v <= d.max());
+            u.push_back(v);
+        }
+        double mean = std::accumulate(u.begin(), u.end(),
+                                              double(0)) / u.size();
+        double var = 0;
+        double skew = 0;
+        double kurtosis = 0;
+        for (int i = 0; i < u.size(); ++i)
+        {
+            double d = (u[i] - mean);
+            double d2 = sqr(d);
+            var += d2;
+            skew += d * d2;
+            kurtosis += d2 * d2;
+        }
+        var /= u.size();
+        double dev = std::sqrt(var);
+        skew /= u.size() * dev * var;
+        kurtosis /= u.size() * var * var;
+        kurtosis -= 3;
+        double x_mean = p.k() * (1 - p.p()) / p.p();
+        double x_var = x_mean / p.p();
+        double x_skew = (2 - p.p()) / std::sqrt(p.k() * (1 - p.p()));
+        double x_kurtosis = 6. / p.k() + sqr(p.p()) / (p.k() * (1 - p.p()));
+        assert(std::abs(mean - x_mean) / x_mean < 0.01);
+        assert(std::abs(var - x_var) / x_var < 0.01);
+        assert(std::abs(skew - x_skew) / x_skew < 0.01);
+        assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.03);
+    }
+}

libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/get_param.pass.cpp

@@ -0,0 +1,29 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class IntType = int>
+// class negative_binomial_distribution
+
+// param_type param() const;
+
+#include <random>
+#include <cassert>
+
+int main()
+{
+    {
+        typedef std::negative_binomial_distribution<> D;
+        typedef D::param_type P;
+        P p(5, .125);
+        D d(p);
+        assert(d.param() == p);
+    }
+}

libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/io.pass.cpp

@@ -0,0 +1,41 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class IntType = int>
+// class negative_binomial_distribution
+
+// template <class charT, class traits>
+// basic_ostream<charT, traits>&
+// operator<<(basic_ostream<charT, traits>& os,
+//            const negative_binomial_distribution& x);
+// 
+// template <class charT, class traits>
+// basic_istream<charT, traits>&
+// operator>>(basic_istream<charT, traits>& is,
+//            negative_binomial_distribution& x);
+
+#include <random>
+#include <sstream>
+#include <cassert>
+
+int main()
+{
+    {
+        typedef std::negative_binomial_distribution<> D;
+        D d1(7, .25);
+        std::ostringstream os;
+        os << d1;
+        std::istringstream is(os.str());
+        D d2;
+        is >> d2;
+        assert(d1 == d2);
+    }
+}

libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/max.pass.cpp

@@ -0,0 +1,27 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class IntType = int>
+// class negative_binomial_distribution
+
+// result_type max() const;
+
+#include <random>
+#include <cassert>
+
+int main()
+{
+    {
+        typedef std::negative_binomial_distribution<> D;
+        D d(4, .25);
+        assert(d.max() == std::numeric_limits<int>::max());
+    }
+}

libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/min.pass.cpp

@@ -0,0 +1,27 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class IntType = int>
+// class negative_binomial_distribution
+
+// result_type min() const;
+
+#include <random>
+#include <cassert>
+
+int main()
+{
+    {
+        typedef std::negative_binomial_distribution<> D;
+        D d(4, .5);
+        assert(d.min() == 0);
+    }
+}

libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/param_assign.pass.cpp

@@ -0,0 +1,32 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class IntType = int>
+// class negative_binomial_distribution
+// {
+//     class param_type;
+
+#include <random>
+#include <limits>
+#include <cassert>
+
+int main()
+{
+    {
+        typedef std::negative_binomial_distribution<> D;
+        typedef D::param_type param_type;
+        param_type p0(6, .7);
+        param_type p;
+        p = p0;
+        assert(p.k() == 6);
+        assert(p.p() == .7);
+    }
+}

libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/param_copy.pass.cpp

@@ -0,0 +1,31 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class IntType = int>
+// class negative_binomial_distribution
+// {
+//     class param_type;
+
+#include <random>
+#include <limits>
+#include <cassert>
+
+int main()
+{
+    {
+        typedef std::negative_binomial_distribution<> D;
+        typedef D::param_type param_type;
+        param_type p0(10, .125);
+        param_type p = p0;
+        assert(p.k() == 10);
+        assert(p.p() == .125);
+    }
+}

libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/param_ctor.pass.cpp

@@ -0,0 +1,44 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class IntType = int>
+// class negative_binomial_distribution
+// {
+//     class param_type;
+
+#include <random>
+#include <limits>
+#include <cassert>
+
+int main()
+{
+    {
+        typedef std::negative_binomial_distribution<> D;
+        typedef D::param_type param_type;
+        param_type p;
+        assert(p.k() == 1);
+        assert(p.p() == 0.5);
+    }
+    {
+        typedef std::negative_binomial_distribution<> D;
+        typedef D::param_type param_type;
+        param_type p(10);
+        assert(p.k() == 10);
+        assert(p.p() == 0.5);
+    }
+    {
+        typedef std::negative_binomial_distribution<> D;
+        typedef D::param_type param_type;
+        param_type p(10, 0.25);
+        assert(p.k() == 10);
+        assert(p.p() == 0.25);
+    }
+}

libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/param_eq.pass.cpp

@@ -0,0 +1,37 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class IntType = int>
+// class negative_binomial_distribution
+// {
+//     class param_type;
+
+#include <random>
+#include <limits>
+#include <cassert>
+
+int main()
+{
+    {
+        typedef std::negative_binomial_distribution<> D;
+        typedef D::param_type param_type;
+        param_type p1(3, 0.75);
+        param_type p2(3, 0.75);
+        assert(p1 == p2);
+    }
+    {
+        typedef std::negative_binomial_distribution<> D;
+        typedef D::param_type param_type;
+        param_type p1(3, 0.75);
+        param_type p2(3, 0.5);
+        assert(p1 != p2);
+    }
+}

libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/param_types.pass.cpp

@@ -0,0 +1,28 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class IntType = int>
+// class negative_binomial_distribution
+// {
+//     class param_type;
+
+#include <random>
+#include <type_traits>
+
+int main()
+{
+    {
+        typedef std::negative_binomial_distribution<> D;
+        typedef D::param_type param_type;
+        typedef param_type::distribution_type distribution_type;
+        static_assert((std::is_same<D, distribution_type>::value), "");
+    }
+}

libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/set_param.pass.cpp

@@ -0,0 +1,30 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class IntType = int>
+// class negative_binomial_distribution
+
+// void param(const param_type& parm);
+
+#include <random>
+#include <cassert>
+
+int main()
+{
+    {
+        typedef std::negative_binomial_distribution<> D;
+        typedef D::param_type P;
+        P p(10, 0.25);
+        D d(8, 0.75);
+        d.param(p);
+        assert(d.param() == p);
+    }
+}

libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/types.pass.cpp

@@ -0,0 +1,32 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class IntType = int>
+// class negative_binomial_distribution
+// {
+//     typedef bool result_type;
+
+#include <random>
+#include <type_traits>
+
+int main()
+{
+    {
+        typedef std::negative_binomial_distribution<> D;
+        typedef D::result_type result_type;
+        static_assert((std::is_same<result_type, int>::value), "");
+    }
+    {
+        typedef std::negative_binomial_distribution<long> D;
+        typedef D::result_type result_type;
+        static_assert((std::is_same<result_type, long>::value), "");
+    }
+}

libcxx/test/numerics/rand/rand.util/rand.util.canonical/generate_canonical.pass.cpp

@@ -15,8 +15,6 @@
 #include <random>
 #include <cassert>
 
-#include <iostream>
-
 int main()
 {
     {