随机前言分析结果如下：请问那些参数表示模型拟合结果的好与坏啊！急急急！

Call:
sfa(formula = log(N) ~ log(D), data = mydata)

Maximum likelihood estimates
(Intercept)       log(D)      sigmaSq        gamma  
   6.554390     0.351602     0.003051     0.879910  
> summary(fit)
Error Components Frontier (see Battese & Coelli 1992)
Inefficiency decreases the endogenous variable (as in a production function)
The dependent variable is logged
Iterative ML estimation terminated after 14 iterations:
cannot find a parameter vector that results in a log-likelihood value
larger than the log-likelihood value obtained in the previous step
Multiplied the initial values 2 time(s) by 0.999 before the search procedure could start
You could try to use different starting values or try to reduce the step size specified in argument 'searchStep'

final maximum likelihood estimates
             Estimate Std. Error z value Pr(>|z|)   
(Intercept) 6.5543904  0.5174872 12.6658  < 2e-16 ***
log(D)      0.3516018  0.1834964  1.9161  0.05535 .  
sigmaSq     0.0030511  0.0048844  0.6247  0.53219   
gamma       0.8799097  0.0427598 20.5780  < 2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
log likelihood value: 14.79821

cross-sectional data
total number of observations = 8

mean efficiency: 0.9478355