/
all_func.cpp
204 lines (181 loc) · 4.26 KB
/
all_func.cpp
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#include <qDebug>
#include "all_func.h"
//Выброчное среднее
double sample_mean(QVector<double> X)
{
double sum=0;
if(X.empty())
{
//throw length_error("sample_mean: error empty vector!");
}
for(auto i : X)
{
sum+=i;
}
return sum/X.size();
}
calc_data do_cucl(int k, int n, double m, double g, QVector<double> trend_m, QVector<double> trend_s,
double level)
{
QVector<QVector<double>> matrix = createMatrix(k,n,m,g,trend_m,trend_s);
QVector<double> y;
for(auto sample : matrix)
{
y.push_back(sample_mean(sample));
}
QVector<double> x;
for(int i = 0; i<k;i++)
{
x.push_back(i);
}
QVector<bool> u = U(y);
QVector<bool> l = L(y);
int a = Asum(u,l);
int b = Bsum(u,l);
//Тренд средних
double F = f(k);
double t_stat_mean = a/F;
double L = l_const(k);
double t_stat_s = (b-F*F)/L;
double t_cr = t_test_cr(k,level);
qDebug() << "a" << a;
qDebug() << "b" << b;
qDebug() << "t mean" << t_stat_mean;
qDebug() << "t s" << t_stat_s;
qDebug() << t_cr;
calc_data data;
data.x=x;
data.y=y;
data.t_A=t_stat_mean;
data.t_B=t_stat_s;
data.t_cr=t_cr;
data.A=a;
data.B=b;
return data;
}
double t_test_cr(int v, double level)
{
double u = quantile(1-level/2);
double q1 = (u*u+1)*u/4;
double q2 = ((5*u*u+16)*pow(u,2) + 3)*u/96;
double q3 = (((3*u*u+19)*u*u+17)*u*u-15)*u/384;
double q4 = ((((79*u*u+776)*u*u + 1482)*u*u -1920)*u*u-945)*u/92160;
double t = u + q1/v + q2/pow(v,2) + q3/pow(v,3) + q4/pow(v,4);
return t;
}
//Расчет квантили норм. распределения.
double quantile(double level)
{
double q, t;
double one = 1;
t = level < 0.5 ? level : one - level;
t = sqrt(-2 * log(t));
q = t - ((0.010328 * t + 0.802853) * t + 2.515517) /
(((0.001308 * t + 0.189269) * t + 1.432788) * t + 1);
return level > 0.5 ? q : -q;
}
double f(int n)
{
return sqrt(2*log(n)-0.8456);
}
double l_const(int n)
{
return sqrt(2*log(n)-3.4253);
}
QVector<bool> U(QVector<double> dynamic_series)
{
QVector<bool> u;
for(int i = 1; i < dynamic_series.size(); i++)
{
bool result=false;
int j = i - 1;
do{
result = dynamic_series[ j ] < dynamic_series[ i ];
j--;
}while(( j>=0 )&&( result ));
u.push_back(result);
}
return u;
}
QVector<bool> L(QVector<double> dynamic_series)
{
QVector<bool> u;
for(int i = 1; i < dynamic_series.size(); i++)
{
bool result=false;
int j = i - 1;
do{
result = dynamic_series[ j ] > dynamic_series[ i ];
j--;
}while(( j>=0 )&&( result ));
u.push_back(result);
}
return u;
}
int A(bool u, bool l)
{
return u-l;
}
int B(bool u,bool l)
{
return u+l;
}
int Asum(QVector<bool> U, QVector<bool> L)
{
int sum = 0;
auto l = L.begin();
for(auto u :U)
{
sum += A(u,*l);
l++;
}
return sum;
}
int Bsum(QVector<bool> U, QVector<bool> L)
{
int sum = 0;
auto l = L.begin();
for(auto u :U)
{
sum += B(u,*l);
l++;
}
return sum;
}
QVector<QVector<double> > createMatrix(int k, int n, double m, double g, QVector<double> trend_mean,
QVector<double> trend_s)
{
QVector<QVector<double> > matrix;
if((trend_mean.size()!=2)||(trend_s.size()!=2))
{
qDebug() << "uncorrect number trend parametr";
return matrix;
}
double mi, gi;
for(int i = 0; i<k; i++)
{
mi = m + trend_mean[0]*i + trend_mean[1]*i*i;
gi = g + trend_s[0]*i + trend_s[1]*i*i;
matrix.push_back(create_sample(n,mi,gi,i));
}
return matrix;
}
QVector<double> create_sample(int size, double m, double g,int k)
{
unsigned seed1 = std::chrono::system_clock::now().time_since_epoch().count()*k;
std::default_random_engine generator(seed1);
std::normal_distribution<double> distribution(m,g);
QVector<double> tmp;
for(int i = 0; i <size; i++)
{
tmp.push_back(distribution(generator));
}
return tmp;
}
void print_v(QVector<bool> v)
{
for(auto e : v)
{
qDebug() << e;
}
}