Overload List
| # | Signature | Description |
|---|---|---|
| 1 | void BetaFit(TVec *X, double &A, double &B, int MaxIter = 500, double Tolerance = 1E-8); | Calculate parameters for Beta distributed values using MLE. |
| 2 | void BetaFit(TVec *X, double &A, double &B, DewArray<double> &PCIA, DewArray<double> &PCIB, int MaxIter = 500, double Tolerance = 1E-8, double Alpha = 0.05); | Calculate parameters for Beta distributed values. |
Overload 1: void BetaFit(TVec *X, double &A, double &B, int MaxIter = 500, double Tolerance = 1E-8);
Calculate parameters for Beta distributed values using MLE.
| # | Name | Type | Description |
|---|---|---|---|
| 1 | X | TVec * | |
| 2 | A | double & | |
| 3 | B | double & | |
| 4 | MaxIter = 500 | int | |
| 5 | Tolerance = 1E-8 | double |
Examples
#include "MtxExpr.h"
#include "Units.StatRandom.h"
#include "Units.Statistics.h"
using namespace Dew;
using namespace Dew::Math;
using namespace Dew::Stats;
using namespace Dew::Stats::Units::StatRandom;
using namespace Dew::Stats::Units::Statistics;
void Example()
{
Vector vec1;
double resA, resB;
DewArray<double> CIA(2), CIB(2);
// first, generate 1000 randomly beta distributed
// numbers with parameters a=3 and b =2
vec1.Size(1000);
RandomBeta(3,2,vec1);
// Now extract the a,b and their 95% confidence intervals.
//Use at max 300 iterations and tolerance 0.001
BetaFit(vec1,resA,resB,CIA,CIB,300,1e-3);
}Declared in Dew::Stats::Units::Statistics · Dew.Stats/Units.Statistics.h · Cross-compiler
Overload 2: void BetaFit(TVec *X, double &A, double &B, DewArray<double> &PCIA, DewArray<double> &PCIB, int MaxIter = 500, double Tolerance = 1E-8, double Alpha = 0.05);
Calculate parameters for Beta distributed values.
| # | Name | Type | Description |
|---|---|---|---|
| 1 | X | TVec * | Stores data which is assumed to be Beta distributed. |
| 2 | A | double & | Return Beta distribution parameter estimator a. |
| 3 | B | double & | Return Beta distribution parameter estimator b. |
| 4 | PCIA | DewArray<double> & | a (1-Alpha)*100 percent confidence interval. |
| 5 | PCIB | DewArray<double> & | b (1-Alpha)*100 percent confidence interval. |
| 6 | MaxIter = 500 | int | Maximum number of iterations needed for deriving a and b. |
| 7 | Tolerance = 1E-8 | double | Defines the acceptable tolerance for calculating a and b. |
| 8 | Alpha = 0.05 | double | Confidence interval percentage. |
Examples
#include <random>
#include "MtxExpr.h"
#include "Units.StatRandom.h"
#include "Units.Statistics.h"
using namespace Dew;
using namespace Dew::Math;
using namespace Dew::Stats;
using namespace Dew::Stats::Units::StatRandom;
using namespace Dew::Stats::Units::Statistics;
void Example()
{
Vector v(1000, false);
// first, generate 1000 randomly beta distributed
// numbers with parameters a = 3 and b = 2
std::random_device rnd;
RandomBeta(3.0, 2.0, v, (int)(rnd() % 2147483647u));
double esta, estb;
DewArray<double> cia(2);
DewArray<double> cib(2);
// Now extract the a,b and their 95% confidence intervals.
//Use at max 300 iterations and tolerance 0.001
BetaFit(v, esta, estb, cia, cib, 300, 1.0e-3, 0.05);
}See Also: RandomBeta, BetaStat
Declared in Dew::Stats::Units::Statistics · Dew.Stats/Units.Statistics.h · Cross-compiler