关于用r语言导出garch拟合值的问题-经管之家官网！

各位大神
主要有两个问题：
1、用r做的GARCH拟合值与用eviews做出的GARCH拟合值不同是什么原因，一些默认方法不同？
2、代码的结果好像和想得到的结果不太一样，想要通过迭代得出最后一个GARCH拟合值组成的序列
部分代码：
library("timeDate")
library("timeSeries")
library("fBasics")
library("fGarch")
local_1_500=c()
for (i in 2:(length(e)-499)){
fm=garchFit(~arma(1,0)+garch(1,1),data=e[i:(i+499)],cond.dist="norm")
local_1_500[(i+499),]=summary(fm)$fitted[,1]
}
得出部分结果：
--- END OF TRACE ---
Time to Estimate Parameters:
Time difference of 0.1404002 secs
Title:
GARCH Modelling
Call:
garchFit(formula = ~arma(1, 0) + garch(1, 1), data = e[i:(i +
499)], cond.dist = "norm")
Mean and Variance Equation:
data ~ arma(1, 0) + garch(1, 1)
<environment: 0x04d03350>
[data = e[i:(i + 499)]]
Conditional Distribution:
norm
Coefficient(s):
mu ar1 omega alpha1 beta1
3.6900e-031.0000e+002.3229e-052.2057e-017.8901e-01
Std. Errors:
based on Hessian
Error Analysis:
EstimateStd. Errort value Pr(>|t|)
mu 3.690e-03 1.212e-03 3.0430.00234 **
ar1 1.000e+00 2.633e-03379.834< 2e-16 ***
omega2.323e-05 NA NA NA
alpha1 2.206e-01 3.569e-03 61.799< 2e-16 ***
beta17.890e-01 9.204e-03 85.722< 2e-16 ***
---
Signif. codes:0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Log Likelihood:
956.6536 normalized:1.913307
Description:
Mon Jul 18 15:33:09 2016 by user: Administrator
Standardised Residuals Tests:
Statistic p-Value
Jarque-Bera Test R Chi^223.920636.392936e-06
Shapiro-Wilk TestR W 0.9893240.001058274
Ljung-Box Test R Q(10)34.197560.0001709915
Ljung-Box Test R Q(15)41.113310.0003073162
Ljung-Box Test R Q(20)43.615110.001694057
Ljung-Box Test R^2Q(10)9.0934940.5232543
Ljung-Box Test R^2Q(15)16.197060.3690775
Ljung-Box Test R^2Q(20)21.464180.3702786
LM Arch Test R TR^2 10.472350.5745945
Information Criterion Statistics:
AIC BIC SIC HQIC
-3.806614 -3.764468 -3.806812 -3.790076
Series Initialization:
ARMA Model: arma
Formula Mean: ~ arma(1, 0)
GARCH Model: garch
Formula Variance: ~ garch(1, 1)
ARMA Order: 1 0
Max ARMA Order: 1
GARCH Order: 1 1
Max GARCH Order: 1
Maximum Order: 1
Conditional Dist: norm
h.start: 2
llh.start: 1
Length of Series: 500
Recursion Init: mci
Series Scale: 0.5386348
错误于arima(.series$x, order = c(u, 0, v), include.mean = include.mean) :
non-stationary AR part from CSS
此外: 共有44个警告 (用warnings()来显示)