帮我看下ARIMA结果

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各位大虾帮俺看看这个分析结果，完全不懂得啥意思
Model Description(a)
Model Name  MOD_3
Dependent Series  Yi
Transformation  None
Independent Series 1 DIFF(Yi,1)
Constant  Included
AR  1
Non-Seasonal Differencing  0
MA  None
Applying the model specifications from MOD_3
a Since there is no seasonal component in the model, the seasonality of the data will be ignored.


Iteration Termination Criteria
Maximum Parameter Change Less Than .001
Maximum Marquardt Constant Greater Than 1000000000
Sum of Squares Percentage Change Less Than .001%
Number of Iterations Equal to 10

Case Processing Summary
Series Length  49
Number of Cases Skipped Due to Missing Values At the Beginning of the Series 2
At the End of the Series 0
Number of Cases with Missing Values within the Series  0(a)
Number of Forecasted Cases  0
Number of New Cases Added to the Current Working File  0
a Melard's Algorithm will be used for estimation.

Requested Initial Configuration
Non-Seasonal Lags AR1 AUTO
Regression Coefficients DIFF(Yi,1) AUTO
Constant  AUTO(a)
a The prior parameter value is invalid and is reset to 0.1.

Iteration History
  Non-Seasonal Lags Regression Coefficients Constant Adjusted Sum of Squares Marquardt Constant
AR1 DIFF(Yi,1)   
0 .779 .486 .005 .115(a) .001
Melard's algorithm was used for estimation.
a The estimation terminated at this iteration, because the sum of squares decreased by less than .001%.

Residual Diagnostics
Number of Residuals 49
Number of Parameters 1
Residual df 46
Adjusted Residual Sum of Squares .115
Residual Sum of Squares .115
Residual Variance .002
Model Std. Error .049
Log-Likelihood 78.857
Akaike's Information Criterion (AIC) -151.714
Schwarz's Bayesian Criterion (BIC) -146.038


Parameter Estimates
    Estimates Std Error t Approx Sig
Non-Seasonal Lags AR1 .779 .090 8.650 .000
Regression Coefficients DIFF(Yi,1) .486 .072 6.795 .000
Constant  .005 .030 .170 .866
Melard's algorithm was used for estimation.


Correlation Matrix
    Non-Seasonal Lags Regression Coefficients Constant
  AR1 DIFF(Yi,1)  
Non-Seasonal Lags AR1 1.000 0(a) 0(a)
Regression Coefficients DIFF(Yi,1) 0(a) 1.000 .021
Constant  0(a) .021 1.000
Melard's algorithm was used for estimation.
a The ARMA parameter estimate and the regression parameter estimate are asymptotically uncorrelated.


Covariance Matrix
    Non-Seasonal Lags Regression Coefficients Constant
  AR1 DIFF(Yi,1)  
Non-Seasonal Lags AR1 .008 0(a) 0(a)
Regression Coefficients DIFF(Yi,1) 0(a) .005 .000
Constant  0(a) .000 .001
Melard's algorithm was used for estimation.
a The ARMA parameter estimate and the regression parameter estimate are asymptotically uncorrelated.

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关键词：ARIMA ima Rim coefficients differencing 结果 ARIMA

你最好用17.0，是中文显示。
意思是进行模型描述。具体内容太多，不便一一陈述。

2# cddingliang
上面是AR(1);ARMA(1,1);ARMA(1,2)的结果，帮我看看，我应该选什么？提示一下哈，帮帮忙，实在没办法进行下去了，我的QQ;459861889