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.