matlab aic sic,请教ADF检验时AIC准则和SIC准则不一致时怎么办?

2022-08-25 13:20:15 浏览数 (1)

大家好,又见面了,我是你们的朋友全栈君。

SIC最小准则下的检验结果如下,显示不能拒绝原假设,即数据有单位根。

Null Hypothesis: LAUS has a unit root

Exogenous: Constant, Linear Trend

Lag Length: 2 (Automatic based on SIC, MAXLAG=11)

t-Statistic Prob.*

Augmented Dickey-Fuller test statistic -2.852264 0.1836

Test critical values: 1% level -4.075340

5% level -3.466248

10% level -3.159780

*MacKinnon (1996) one-sided p-values.

Augmented Dickey-Fuller Test Equation

Dependent Variable: D(LAUS)

Method: Least Squares

Date: 04/19/10 Time: 00:29

Sample (adjusted): 2003M06 2010M02

Included observations: 81 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

LAUS(-1) -0.096154 0.033711 -2.852264 0.0056

D(LAUS(-1)) 0.277307 0.107765 2.573249 0.0120

D(LAUS(-2)) 0.267434 0.112258 2.382311 0.0197

C 0.358679 0.120148 2.985296 0.0038

@TREND(2003M03) 0.001129 0.000629 1.793788 0.0768

R-squared 0.232264 Mean dependent var 0.017248

Adjusted R-squared 0.191857 S.D. dependent var 0.092995

S.E. of regression 0.083600 Akaike info criterion -2.065816

Sum squared resid 0.531155 Schwarz criterion -1.918011

Log likelihood 88.66555 Hannan-Quinn criter. -2.006515

F-statistic 5.748106 Durbin-Watson stat 2.022050

Prob(F-statistic) 0.000427

AIC最小准则下的检验结果如下,显示可以拒绝原假设,即数据是平稳的。

Null Hypothesis: LAUS has a unit root

Exogenous: Constant, Linear Trend

Lag Length: 11 (Automatic based on AIC, MAXLAG=11)

t-Statistic Prob.*

Augmented Dickey-Fuller test statistic -3.667550 0.0311

Test critical values: 1% level -4.090602

5% level -3.473447

10% level -3.163967

*MacKinnon (1996) one-sided p-values.

Augmented Dickey-Fuller Test Equation

Dependent Variable: D(LAUS)

Method: Least Squares

Date: 04/19/10 Time: 00:32

Sample (adjusted): 2004M03 2010M02

Included observations: 72 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

LAUS(-1) -0.228708 0.062360 -3.667550 0.0005

D(LAUS(-1)) 0.380046 0.117766 3.227139 0.0021

D(LAUS(-2)) 0.293686 0.129738 2.263681 0.0274

D(LAUS(-3)) 0.169357 0.130475 1.298002 0.1994

D(LAUS(-4)) 0.082224 0.119306 0.689182 0.4935

D(LAUS(-5)) 0.211606 0.120553 1.755286 0.0845

D(LAUS(-6)) -0.006804 0.117780 -0.057770 0.9541

D(LAUS(-7)) 0.348143 0.117460 2.963938 0.0044

D(LAUS(-8)) -0.213273 0.125900 -1.693992 0.0956

D(LAUS(-9)) -0.003686 0.129064 -0.028562 0.9773

D(LAUS(-10)) 0.070850 0.129564 0.546836 0.5866

D(LAUS(-11)) 0.390049 0.130423 2.990637 0.0041

C 0.796047 0.216183 3.682283 0.0005

@TREND(2003M03) 0.003431 0.001065 3.222824 0.0021

R-squared 0.442577 Mean dependent var 0.011301

Adjusted R-squared 0.317638 S.D. dependent var 0.096100

S.E. of regression 0.079384 Akaike info criterion -2.056378

Sum squared resid 0.365504 Schwarz criterion -1.613693

Log likelihood 88.02962 Hannan-Quinn criter. -1.880144

F-statistic 3.542333 Durbin-Watson stat 2.074039

Prob(F-statistic) 0.000431

发布者:全栈程序员栈长,转载请注明出处:https://javaforall.cn/142356.html原文链接:https://javaforall.cn

0 人点赞