C++ Matrix::AsColumn方法代码示例

void trymat7()
{
//   cout << "\nSeventh test of Matrix package\n";
    Tracer et("Seventh test of Matrix package");
    Tracer::PrintTrace();

    int i,j;


    DiagonalMatrix D(6);
    UpperTriangularMatrix U(6);
    for (i=1; i<=6; i++) {
        for (j=i; j<=6; j++) U(i,j)=i*i*j-50;
        D(i,i)=i*i+i-10;
    }
    LowerTriangularMatrix L=(U*3.0).t();
    SymmetricMatrix S(6);
    for (i=1; i<=6; i++) for (j=i; j<=6; j++) S(i,j)=i*i+2.0+j;
    Matrix MD=D;
    Matrix ML=L;
    Matrix MU=U;
    Matrix MS=S;
    Matrix M(6,6);
    for (i=1; i<=6; i++) for (j=1; j<=6; j++) M(i,j)=i*j+i*i-10.0;
    {
        Tracer et1("Stage 1");
        Print(Matrix((S-M)-(MS-M)));
        Print(Matrix((-M-S)+(MS+M)));
        Print(Matrix((U-M)-(MU-M)));
    }
    {
        Tracer et1("Stage 2");
        Print(Matrix((L-M)+(M-ML)));
        Print(Matrix((D-M)+(M-MD)));
        Print(Matrix((D-S)+(MS-MD)));
        Print(Matrix((D-L)+(ML-MD)));
    }

    {
        M=MU.t();
    }
    LowerTriangularMatrix LY=D.i()*U.t();
    {
        Tracer et1("Stage 3");
        MS=D*LY-M;
        Clean(MS,0.00000001);
        Print(MS);
        L=U.t();
        LY=D.i()*L;
        MS=D*LY-M;
        Clean(MS,0.00000001);
        Print(MS);
    }
    {
        Tracer et1("Stage 4");
        UpperTriangularMatrix UT(11);
        int i, j;
        for (i=1; i<=11; i++) for (j=i; j<=11; j++) UT(i,j)=i*i+j*3;
        GenericMatrix GM;
        Matrix X;
        UpperBandMatrix UB(11,3);
        UB.Inject(UT);
        UT = UB;
        UpperBandMatrix UB2 = UB / 8;
        GM = UB2-UT/8;
        X = GM;
        Print(X);
        SymmetricBandMatrix SB(11,4);
        SB << (UB + UB.t());
        X = SB - UT - UT.t();
        Print(X);
        BandMatrix B = UB + UB.t()*2;
        DiagonalMatrix D;
        D << B;
        X.ReSize(1,1);
        X(1,1) = Trace(B)-Sum(D);
        Print(X);
        X = SB + 5;
        Matrix X1=X;
        X = SP(UB,X);
        Matrix X2 =UB;
        X1 = (X1.AsDiagonal() * X2.AsDiagonal()).AsRow()-X.AsColumn().t();
        Print(X1);
        X1=SB.t();
        X2 = B.t();
        X = SB.i() * B - X1.i() * X2.t();
        Clean(X,0.00000001);
        Print(X);
        X = SB.i();
        X = X * B - X1.i() * X2.t();
        Clean(X,0.00000001);
        Print(X);
        D = 1;
        X = SB.i() * SB - D;
        Clean(X,0.00000001);
        Print(X);
        ColumnVector CV(11);
        CV << 2 << 6 <<3 << 8 << -4 << 17.5 << 2 << 1 << -2 << 5 << 3.75;
        D << 2 << 6 <<3 << 8 << -4 << 17.5 << 2 << 1 << -2 << 5 << 3.75;
        X = CV.AsDiagonal();
//.........这里部分代码省略.........

//extern "C"
SEXP mc_irf_var(SEXP varobj, SEXP nsteps, SEXP draws)
{
  int m, p, dr=INTEGER(draws)[0], ns=INTEGER(nsteps)[0], T, df, i;
  SEXP AR, Y, Bhat, XR, prior, hstar, meanS, output;

  // Get # vars/lags/steps/draws/T/df
  PROTECT(AR = listElt(varobj, "ar.coefs"));
  PROTECT(Y = listElt(varobj, "Y"));
  m = INTEGER(getAttrib(AR, R_DimSymbol))[0]; //#vars
  p = INTEGER(getAttrib(AR, R_DimSymbol))[2]; //#lags
  T = nrows(Y); df = T - m*p - m - 1;
  UNPROTECT(2);

  // Put coefficients from varobj$Bhat in Bcoefs vector (m^2*p, 1)
  PROTECT(Bhat = coerceVector(listElt(varobj, "Bhat"), REALSXP));
  Matrix bcoefs = R2Cmat(Bhat, m*p, m);
  bcoefs = bcoefs.AsColumn();
  UNPROTECT(1);

  // Define X(T x m*p) subset of varobj$X and XXinv as solve(X'X)
  PROTECT(XR = coerceVector(listElt(varobj,"X"),REALSXP));
  Matrix X = R2Cmat(XR, T, m*p), XXinv;
  UNPROTECT(1);

  // Get the correct moment matrix
  PROTECT(prior = listElt(varobj,"prior"));
  if(!isNull(prior)){
    PROTECT(hstar = coerceVector(listElt(varobj,"hstar"),REALSXP));
    XXinv = R2Cmat(hstar, m*p, m*p).i();
    UNPROTECT(1);
  }
  else { XXinv = (X.t()*X).i(); }
  UNPROTECT(1);

  // Get the transpose of the Cholesky decomp of XXinv
  SymmetricMatrix XXinvSym; XXinvSym << XXinv;
  XXinv = Cholesky(XXinvSym);

  // Cholesky of covariance
  PROTECT(meanS = coerceVector(listElt(varobj,"mean.S"),REALSXP));
  SymmetricMatrix meanSSym; meanSSym << R2Cmat(meanS, m, m);
  Matrix Sigmat = Cholesky(meanSSym);
  UNPROTECT(1);

  // Matricies needed for the loop
  ColumnVector bvec; bvec=0.0;
  Matrix sqrtwish, impulse(dr,m*m*ns); impulse = 0.0;
  SymmetricMatrix sigmadraw; sigmadraw = 0.0;
  IdentityMatrix I(m);

  GetRNGstate();
  // Main Loop
  for (i=1; i<=dr; i++){
    // Wishart/Beta draws
    sigmadraw << Sigmat*(T*rwish(I,df).i())*Sigmat.t();
    sqrtwish = Cholesky(sigmadraw);
    bvec = bcoefs+KP(sqrtwish, XXinv)*rnorms(m*m*p);

    // IRF computation
    impulse.Row(i) = irf_var_from_beta(sqrtwish, bvec, ns).t();
    if (!(i%1000)){ Rprintf("Monte Carlo IRF Iteration = %d\n",i); }
  } // end main loop
  PutRNGstate();

  int dims[]={dr,ns,m*m};
  PROTECT(output = C2R3D(impulse,dims));
  setclass(output,"mc.irf.VAR");
  UNPROTECT(1);
  return output;
}