XtX = sackmat_m.make_zero_matrix(k, k) for i in range(0, k): xi = xs[i] for j in range(i, k): xj = xs[j] xi_dot_xj = sackmat_m.vecdot(xi, xj) XtX[i][j] = xi_dot_xj if i != j: XtX[j][i] = xi_dot_xj # 3. commpute XxT.inv XtXi = XtX.inv() # xxx handle singular ... # 4. commpute XtX.inv Xt y Xt = sackmat_m.sackmat(xs) X = Xt.transpose() beta_hat = XtXi * Xt * y print 'beta_hat: ' print beta_hat print # 5. Estimate eps X_beta_hat = X * beta_hat eps_hat = sackmat_m.vecsub(y, X_beta_hat) #print 'eps_hat ' #print eps_hat #print # 6. Estimate V
XtX = sackmat_m.make_zero_matrix(k, k)
for i in range(0, k):
xi = xs[i]
for j in range(i, k):
xj = xs[j]
xi_dot_xj = sackmat_m.vecdot(xi, xj)
XtX[i][j] = xi_dot_xj
if i != j:
XtX[j][i] = xi_dot_xj
# 3. commpute XxT.inv
XtXi = XtX.inv()
# xxx handle singular ...
# 4. commpute XtX.inv Xt y
Xt = sackmat_m.sackmat(xs)
X = Xt.transpose()
beta_hat = XtXi * Xt * y
print 'beta_hat: '
print beta_hat
print
# 5. Estimate eps
X_beta_hat = X * beta_hat
eps_hat = sackmat_m.vecsub(y, X_beta_hat)
#print 'eps_hat '
#print eps_hat
#print
# 6. Estimate V
def pqmat(p, q): return sackmat_m.sackmat([[p, 1-p],[1-q, q]])