请问在R中，用随机前言分析，进行回归，得出如下结果，怎样分析拟合结果的好坏，如sigmaSq 、 gamma、log likelihood value、mean efficiency，怎样解读这些指标。急需解释，非常感谢！
数据输入代码如下：
mydata<-read.table(file="clipboard",sep="\t",header=T)
mydata

library(frontier)
fit<-sfa(log(N)~log(D),data=mydata)
fit
summary(fit)
拟合结果如下：
fit

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

Maximum likelihood estimates
(Intercept)       log(D)      sigmaSq        gamma  
  8.730e+00   -4.214e-01    2.079e-03    2.015e-05  
> 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 47 iterations:
log likelihood values and parameters of two successive iterations
are within the tolerance limit

final maximum likelihood estimates
               Estimate  Std. Error z value  Pr(>|z|)   
(Intercept)  8.7298e+00  2.9557e-01 29.5356 < 2.2e-16 ***
log(D)      -4.2145e-01  9.1244e-02 -4.6189 3.858e-06 ***
sigmaSq      2.0791e-03  8.0184e-04  2.5929  0.009518 **
gamma        2.0148e-05  3.5018e-02  0.0006  0.999541   
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
log likelihood value: 23.36575

cross-sectional data
total number of observations = 14
mean efficiency: 0.9998367