我试图检查Stata是否在我以前的reg使用的模型NormalReg(样本模型)中取得初始值。但是，在我看来，第0次迭代没有考虑到我的初始值。任何帮助解决这个问题将不胜感激。在Stata中设置ML编程的初始值

set seed 123

set obs 1000

gen x = runiform()*2

gen u = rnormal()*5

gen y = 2 + 2*x + u

reg y x

Source | SS df MS Number of obs = 1000

-------------+------------------------------ F( 1, 998) = 52.93

Model | 1335.32339 1 1335.32339 Prob > F = 0.0000

Residual | 25177.012 998 25.227467 R-squared = 0.0504

-------------+------------------------------ Adj R-squared = 0.0494

Total | 26512.3354 999 26.5388743 Root MSE = 5.0227

------------------------------------------------------------------------------

y | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------

x | 1.99348 .2740031 7.28 0.000 1.455792 2.531168

_cons | 2.036442 .3155685 6.45 0.000 1.417188 2.655695

------------------------------------------------------------------------------

cap program drop NormalReg

program define NormalReg

args lnlk xb sigma2

qui replace `lnlk' = -ln(sqrt(`sigma2'*2*_pi)) - ($ML_y-`xb')^2/(2*`sigma2')

end

ml model lf NormalReg (reg: y = x) (sigma2:)

ml init reg:x = `=_b[x]'

ml init reg:_cons = `=_b[_cons]'

ml max,iter(1) trace

ml max,iter(1) trace

initial: log likelihood = - (could not be evaluated)

searching for feasible values .+

feasible: log likelihood = -28110.03

rescaling entire vector .+.

rescale: log likelihood = -14623.922

rescaling equations ...+++++.

rescaling equations ....

rescale eq: log likelihood = -3080.0872

------------------------------------------------------------------------------

Iteration 0:

Parameter vector:

reg: reg: sigma2:

x _cons _cons

r1 3.98696 1 32

log likelihood = -3080.0872

------------------------------------------------------------------------------

Iteration 1:

Parameter vector:

reg: reg: sigma2:

x _cons _cons

r1 2.498536 1.773872 24.10726

log likelihood = -3035.3553

------------------------------------------------------------------------------

convergence not achieved

Number of obs = 1000

Wald chi2(1) = 86.45

Log likelihood = -3035.3553 Prob > chi2 = 0.0000

------------------------------------------------------------------------------

y | Coef. Std. Err. z P>|z| [95% Conf. Interval]

-------------+----------------------------------------------------------------

reg |

x | 2.498536 .2687209 9.30 0.000 1.971853 3.02522

_cons | 1.773872 .3086854 5.75 0.000 1.16886 2.378885

-------------+----------------------------------------------------------------

sigma2 |

_cons | 24.10726 1.033172 23.33 0.000 22.08228 26.13224

------------------------------------------------------------------------------

Warning: convergence not achieved

2013-11-27

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