STK++ 0.9.13
Functions
tutoStatCovariance.cpp File Reference
#include "STKpp.h"
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int main (int argc, char **argv)
 

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◆ main()

int main ( int  argc,
char **  argv 
)

Definition at line 4 of file tutoStatCovariance.cpp.

5{
6 // create coovariance matrix and its Cholesky decomposition
7 CArraySquare<Real, 3> s; s << 2.0, 0.8, 0.36,
8 0.8, 2.0, 0.8,
9 0.36,0.8, 1.0;
10 Array2DLowerTriangular<Real> L; Array2DDiagonal<Real> D;
11 cholesky(s, D, L);
12 // create correlated data set
13 CArray<Real, 100, 3> a;
14 a = a.randGauss() * D.sqrt() * L.transpose() + 1;
15 stk_cout << "True sigma=\n" << s;
16 stk_cout << "Estimated sigma=\n" << Stat::covariance(a);
17 return 0;
18}
stk_cout
#define stk_cout
Standard stk output stream.
Definition STK_Typedefs.h:73
STK::MultidimRegression
The MultidimRegression class allows to regress a multidimensional output variable among a multivariat...
Definition STK_MultidimRegression.h:52
STK::cholesky
bool cholesky(ExprBase< Lhs > const &A, Array2DDiagonal< typename Lhs::Type > &D, Array2DLowerTriangular< typename Lhs::Type > &L)
Compute the Cholesky decomposition of a symmetric matrix.
Definition STK_Cholesky.h:63
STK::Stat::covariance
Real covariance(ExprBase< XArray > const &X, ExprBase< YArray > const &Y, bool unbiased=false)
Compute the covariance of the variables X and Y.
Definition STK_Stat_Covariance.h:55

References STK::cholesky(), STK::Stat::covariance(), STK::ArrayBase< Derived >::randGauss(), STK::ExprBase< Derived >::sqrt(), stk_cout, and STK::ArrayBase< Derived >::transpose().