ROL
ROL_Kumaraswamy.hpp
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43
44#ifndef ROL_KUMARASWAMY_HPP
45#define ROL_KUMARASWAMY_HPP
46
47#include "ROL_Distribution.hpp"
48#include "ROL_ParameterList.hpp"
49
50#include <math.h>
51
52namespace ROL {
53
54template<class Real>
55class Kumaraswamy : public Distribution<Real> {
56private:
57 Real a_;
58 Real b_;
59 Real exp1_;
60 Real exp2_;
62
63 size_t nchoosek(const size_t n, const size_t k) const {
64 return ((k==0) ? 1 : (n*nchoosek(n-1,k-1))/k);
65 }
66
67public:
68 Kumaraswamy(const Real a = 0., const Real b = 1.,
69 const Real exp1 = 0.5, const Real exp2 = 0.5)
70 : a_(std::min(a,b)), b_(std::max(a,b)),
71 exp1_((exp1>0.) ? exp1 : 0.5), exp2_((exp2>0.) ? exp2 : 0.5) {
72 bGAMMAb_ = exp2_*tgamma(exp2_);
73 }
74
75 Kumaraswamy(ROL::ParameterList &parlist) {
76 a_ = parlist.sublist("SOL").sublist("Distribution").sublist("Kumaraswamy").get("Lower Bound",0.);
77 b_ = parlist.sublist("SOL").sublist("Distribution").sublist("Kumaraswamy").get("Upper Bound",1.);
78 Real tmp = a_;
79 a_ = std::min(a_,b_);
80 b_ = std::max(b_,tmp);
81
82 exp1_ = parlist.sublist("SOL").sublist("Distribution").sublist("Kumaraswamy").get("Exponent 1",0.5);
83 exp2_ = parlist.sublist("SOL").sublist("Distribution").sublist("Kumaraswamy").get("Exponent 2",0.5);
84 exp1_ = (exp1_ > 0.) ? exp1_ : 0.5;
85 exp2_ = (exp2_ > 0.) ? exp2_ : 0.5;
86
87 bGAMMAb_ = exp2_*tgamma(exp2_);
88 }
89
90 Real evaluatePDF(const Real input) const {
91 Real x = (input - a_)/(b_-a_);
92 return ((x <= 0.) ? 0. : ((x >= 1.) ? 0. :
93 exp1_*exp2_*std::pow(x,exp1_-1)*std::pow(1.-std::pow(x,exp1_),exp2_-1)));
94 }
95
96 Real evaluateCDF(const Real input) const {
97 Real x = (input - a_)/(b_-a_);
98 return ((x <= 0.) ? 0. : ((x >= 1.) ? 1. : 1.-std::pow(1.-std::pow(x,exp1_),exp2_)));
99 }
100
101 Real integrateCDF(const Real input) const {
102 ROL_TEST_FOR_EXCEPTION( true, std::invalid_argument,
103 ">>> ERROR (ROL::Kumaraswamy): Kumaraswamy integrateCDF not implemented!");
104 }
105
106 Real invertCDF(const Real input) const {
107 Real x = std::pow(1.-std::pow(1.-input,1./exp2_),1./exp1_);
108 return x*(b_-a_) + a_;
109 }
110
111 Real moment(const size_t m) const {
112 Real val = 0., binom = 0., moment = 0.;
113 for (size_t i = 0; i < m+1; i++) {
114 moment = bGAMMAb_*tgamma(1.+(Real)i/exp1_)/tgamma(1.+exp2_+(Real)i/exp1_);
115 binom = (Real)nchoosek(m,i);
116 val += binom*std::pow(a_,m-i)*std::pow(b_-a_,i+1)*moment;
117 }
118 return val;
119 }
120
121 Real lowerBound(void) const {
122 return a_;
123 }
124
125 Real upperBound(void) const {
126 return b_;
127 }
128
129 void test(std::ostream &outStream = std::cout ) const {
130 size_t size = 5;
131 std::vector<Real> X(size,0.);
132 std::vector<int> T(size,0);
133 X[0] = a_-4.*(Real)rand()/(Real)RAND_MAX;
134 T[0] = 0;
135 X[1] = a_;
136 T[1] = 1;
137 X[2] = (b_-a_)*(Real)rand()/(Real)RAND_MAX + a_;
138 T[2] = 0;
139 X[3] = b_;
140 T[3] = 1;
141 X[4] = b_+4.0*(Real)rand()/(Real)RAND_MAX;
142 T[4] = 0;
143 Distribution<Real>::test(X,T,outStream);
144 }
145};
146
147}
148
149#endif
virtual void test(std::ostream &outStream=std::cout) const
Real moment(const size_t m) const
Real integrateCDF(const Real input) const
Real upperBound(void) const
Kumaraswamy(ROL::ParameterList &parlist)
size_t nchoosek(const size_t n, const size_t k) const
Real evaluatePDF(const Real input) const
Real evaluateCDF(const Real input) const
Real lowerBound(void) const
void test(std::ostream &outStream=std::cout) const
Real invertCDF(const Real input) const
Kumaraswamy(const Real a=0., const Real b=1., const Real exp1=0.5, const Real exp2=0.5)