What is the null hypothesis of the Dickey Fuller test for testing with a constant and a trend?
The null hypothesis of DF test is that there is a unit root in an AR model, which implies that the data series is not stationary. The alternative hypothesis is generally stationarity or trend stationarity but can be different depending on the version of the test is being used.
What is the null hypothesis of the Dickey Fuller test for testing with no constant and no trend?
In statistics, the Dickey–Fuller test tests the null hypothesis that a unit root is present in an autoregressive time series model. The alternative hypothesis is different depending on which version of the test is used, but is usually stationarity or trend-stationarity.
Is the KPSS test the same as the ADF test?
A function is created to carry out the ADF test on a time series. KPSS is another test for checking the stationarity of a time series. The null and alternate hypothesis for the KPSS test are opposite that of the ADF test. Null Hypothesis: The process is trend stationary.
How to reject h 0 and KPSS test?
KPSS test: don`t reject H 0. Both imply that series is stationary. Case 3 If we can’t reject both test: data give not enough observations. Case 4 Reject unit root, reject stationarity: both hypothesis are component hypothesis – heteroskedasticity in series may make a big difference; if there is structural break it will affect inference.
What are the results of the KPSS test?
The KPSS tests gives the following results – test statistic, p value and the critical value at 1%, 5% , and 10% confidence intervals. KPSS test is now applied on the data. [8]: kpss_test(sunspots[‘SUNACTIVITY’]) Results of KPSS Test: Test Statistic 0.669866 p-value 0.016285 Lags Used 7.000000 Critical Value (10%) 0.347000 Critical Value (5%)
What are the results of the ADF test?
The ADF tests gives the following results – test statistic, p value and the critical value at 1%, 5% , and 10% confidence intervals. ADF test is now applied on the data.