[img]file:///C:\Users\huangshuzhen\AppData\Roaming\Tencent\Users\443057247\QQ\WinTemp\RichOle\3_@_`R~9}L]VQ1[{GD5FV2W.png[/img]有没有小伙伴知道这个结果是否合理？为什么跑出来的结果值迭代了1次啊，有没有人遇到一样的问题啊，求解[img]file:///C:\Users\HUANGS~1\AppData\Local\Temp\52W[C~~FFQ[27)18U93ZOWB.gif[/img][img]file:///C:\Users\HUANGS~1\AppData\Local\Temp\52W[C~~FFQ[27)18U93ZOWB.gif[/img]
the ols estimates are :
coefficient standard-error t-ratio
beta 0 0.71979299E-02 0.40170706E-02 0.17918356E+01
beta 1 0.27192751E-06 0.10641503E-06 0.25553486E+01
beta 2 -0.62320020E-06 0.38559531E-06 -0.16162028E+01
sigma-squared 0.15993184E-02
log likelihood function = 0.13606165E+04
the estimates after the grid search were :
beta 0 -0.38436154E-01
beta 1 0.27192751E-06
beta 2 -0.62320020E-06
sigma-squared 0.36754330E-02
gamma 0.89000000E+00
mu is restricted to be zero
eta is restricted to be zero
iteration = 0 func evals = 20 llf = 0.15456902E+04
-0.38436154E-01 0.27192751E-06-0.62320020E-06 0.36754330E-02 0.89000000E+00
gradient step
pt better than entering pt cannot be found
iteration = 1 func evals = 28 llf = 0.15456902E+04
-0.38436154E-01 0.27192751E-06-0.62320020E-06 0.36754330E-02 0.89000000E+00
the final mle estimates are :
coefficient standard-error t-ratio
beta 0 -0.38436154E-01 0.10000000E+01 -0.38436154E-01
beta 1 0.27192751E-06 0.10000000E+01 0.27192751E-06
beta 2 -0.62320020E-06 0.10000000E+01 -0.62320020E-06
sigma-squared 0.36754330E-02 0.10000000E+01 0.36754330E-02
gamma 0.89000000E+00 0.10000000E+01 0.89000000E+00
mu is restricted to be zero
eta is restricted to be zero
log likelihood function = 0.15456902E+04
LR test of the one-sided error = 0.37014737E+03
with number of restrictions = 1
[note that this statistic has a mixed chi-square distribution]
[img]file:///C:\Users\huangshuzhen\AppData\Roaming\Tencent\Users\443057247\QQ\WinTemp\RichOle\3_@_`R~9}L]VQ1[{GD5FV2W.png[/img]
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