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雷达卡
本人最近在学习使用Frontier4.1，之前没有什么数学基础完全看不懂 那个输出结果再说什么啊，我们只是要研究一个 一元线性方程 y=af(x)+b的边界线，求解释，输出结果里面哪个是a,b的值。
如果都没有，那么那个输出结果到底再说什么，附上EG1-OUT的数据，求大神解释，谢谢，另附上我的QQ 276970540如果能细心指教万分感谢。
Output from the program FRONTIER (Version 4.1c)
instruction file = Eg1-ins.txt
data file = eg1-dta.txt
Error Components Frontier (see B&C 1992)
The model is a production function
The dependent variable is logged
the ols estimates are :
coefficient standard-error t-ratio
beta 0 0.24489834E+00 0.21360307E+00 0.11465114E+01
beta 1 0.28049246E+00 0.48066617E-01 0.58354940E+01
beta 2 0.53330637E+00 0.51498586E-01 0.10355748E+02
sigma-squared 0.11398496E+00
log likelihood function = -0.18446849E+02
the estimates after the grid search were :
beta 0 0.58014216E+00
beta 1 0.28049246E+00
beta 2 0.53330637E+00
sigma-squared 0.22067413E+00
gamma 0.80000000E+00
mu is restricted to be zero
eta is restricted to be zero
iteration = 0 func evals = 20 llf = -0.17034854E+02
0.58014216E+00 0.28049246E+00 0.53330637E+00 0.22067413E+00 0.80000000E+00
gradient step
iteration = 5 func evals = 42 llf = -0.17027230E+02
0.56160697E+00 0.28108701E+00 0.53647803E+00 0.21694170E+00 0.79718731E+00
pt better than entering pt cannot be found
iteration = 7 func evals = 69 llf = -0.17027229E+02
0.56161963E+00 0.28110205E+00 0.53647981E+00 0.21700046E+00 0.79720730E+00
the final mle estimates are :
coefficient standard-error t-ratio
beta 0 0.56161963E+00 0.20261668E+00 0.27718331E+01
beta 1 0.28110205E+00 0.47643365E-01 0.59001301E+01
beta 2 0.53647981E+00 0.45251553E-01 0.11855501E+02
sigma-squared 0.21700046E+00 0.63909106E-01 0.33954545E+01
gamma 0.79720730E+00 0.13642399E+00 0.58436004E+01
mu is restricted to be zero
eta is restricted to be zero
log likelihood function = -0.17027229E+02
LR test of the one-sided error = 0.28392402E+01
with number of restrictions = 1
[note that this statistic has a mixed chi-square distribution]
number of iterations = 7
(maximum number of iterations set at : 100)
number of cross-sections = 60
number of time periods = 1
total number of observations = 60
thus there are: 0 obsns not in the panel
covariance matrix :
0.41053521E-01 -0.31446721E-02 -0.80030279E-02 0.40456494E-02 0.92519362E-02
-0.31446721E-02 0.22698902E-02 0.40106205E-04 -0.29528845E-04 -0.91550467E-04
-0.80030279E-02 0.40106205E-04 0.20477030E-02 -0.47190308E-04 -0.16404645E-03
0.40456494E-02 -0.29528845E-04 -0.47190308E-04 0.40843738E-02 0.67450773E-02
0.92519362E-02 -0.91550467E-04 -0.16404645E-03 0.67450773E-02 0.18611506E-01
technical efficiency estimates :
firm eff.-est.
1 0.65068880E+00
2 0.82889151E+00
3 0.72642592E+00
4 0.74785113E+00
5 0.69133584E+00
6 0.77654637E+00
7 0.56516787E+00
8 0.73768185E+00
9 0.84388964E+00
10 0.75784167E+00
11 0.54558432E+00
12 0.93739520E+00
13 0.44809682E+00
14 0.61831027E+00
15 0.87384359E+00
16 0.54952777E+00
17 0.71262499E+00
18 0.75907226E+00
19 0.85727198E+00
20 0.80651927E+00
21 0.72458613E+00
22 0.87223606E+00
23 0.83681369E+00
24 0.75225715E+00
25 0.52974774E+00
26 0.89731683E+00
27 0.81013415E+00
28 0.78179413E+00
29 0.85610585E+00
30 0.62097885E+00
31 0.57938181E+00
32 0.74934194E+00
33 0.88192581E+00
34 0.42082174E+00
35 0.35126244E+00
36 0.88908382E+00
37 0.84118609E+00
38 0.67868899E+00
39 0.67291047E+00
40 0.83853427E+00
41 0.75964587E+00
42 0.68189614E+00
43 0.80438742E+00
44 0.88652992E+00
45 0.74299265E+00
46 0.72610191E+00
47 0.85341515E+00
48 0.78519185E+00
49 0.67207111E+00
50 0.51430249E+00
51 0.84238134E+00
52 0.85098581E+00
53 0.85963850E+00
54 0.75508293E+00
55 0.81649829E+00
56 0.75991250E+00
57 0.87350729E+00
58 0.66471456E+00
59 0.85670448E+00
60 0.70842786E+00
mean efficiency = 0.74056772E+00
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