本人在stata中做了一个非线性arch的估计（higgins and bera 1992）。怎么用公式表示呢？那个指数怎么确定？

. arch r1, narch(1/2) garch(1/1)

(setting optimization to BHHH)
Iteration 0: log likelihood = -1599.2632
Iteration 1: log likelihood = -1574.4013
Iteration 2: log likelihood = -1573.8612
Iteration 3: log likelihood = -1572.4468
Iteration 4: log likelihood = -1563.6917
(switching optimization to BFGS)
Iteration 5: log likelihood = -1538.7726
Iteration 6: log likelihood = -1533.6418
Iteration 7: log likelihood = -1529.8792
Iteration 8: log likelihood = -1528.6739
Iteration 9: log likelihood = -1528.0528
Iteration 10: log likelihood = -1527.485
Iteration 11: log likelihood = -1527.0405
Iteration 12: log likelihood = -1526.8679
Iteration 13: log likelihood = -1526.7005
Iteration 14: log likelihood = -1526.5504
(switching optimization to BHHH)
Iteration 15: log likelihood = -1526.0572
Iteration 16: log likelihood = -1525.5523
Iteration 17: log likelihood = -1525.45
Iteration 18: log likelihood = -1525.4064
Iteration 19: log likelihood = -1525.3829
(switching optimization to BFGS)
Iteration 20: log likelihood = -1525.3717
Iteration 21: log likelihood = -1525.3605
Iteration 22: log likelihood = -1525.36
Iteration 23: log likelihood = -1525.3599
Iteration 24: log likelihood = -1525.3599

ARCH family regression

Sample: 2 to 916 Number of obs = 915
Wald chi2(.) = .
Log likelihood = -1525.36 Prob > chi2 = .

------------------------------------------------------------------------------
| OPG
r1 | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
r1 |
_cons | -.1340951 .0412149 -3.25 0.001 -.2148748 -.0533154
-------------+----------------------------------------------------------------
ARCH |
narch |
L1. | .0916207 .0220403 4.16 0.000 .0484225 .1348189
L2. | .1250781 .0407443 3.07 0.002 .0452207 .2049356
narch_k |
L1. | -.2175358 .3477103 -0.63 0.532 -.8990353 .4639638
L2. | 1.304588 .3560714 3.66 0.000 .6067012 2.002475
garch |
L1. | .6653135 .0467304 14.24 0.000 .5737237 .7569034
_cons | .0417348 .0930887 0.45 0.654 -.1407157 .2241853
------------------------------------------------------------------------------