Dickey Fuller Test Sine Wave or seasonallity

In summary, the conversation is about the application and validity of the Dickey Fuller test. The person is asking if they need to account for seasonality when performing the test using a sine wave. They also mention receiving a value of 1 for hd and being able to reject the unit root hypothesis, but are unsure if this makes sense. They are also wondering if they need to pre-process their data to remove seasonality and how many lags they should keep. They apologize for not being able to find answers and ask for additional information.
  • #1
EmmaSaunders1
45
0
Hi can someone please clarify info regarding the application and validity of the Dickey Fuller test.

If I perform the test using a sine wave would I be required to somehow take into account the seasonality. From my understanding a sine wave is non stationary, using the MATLAB command below I receive a value for hd of 1 and therefore can reject the unit root hypothesis and thus the signal is stationary, does this make sense? I have searched for answers to no avail.

[hd pValue]=adftest(sin(0:0.1:300));

In general I have some pseudo oscillatory data and do not know if I need to pre-process the data to remove seasonality before performing this test? If someone could enlighten me on the amount of lags I am required to keep that would also be great.

Thanks for any help
 
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  • #2
I'm sorry you are not finding help at the moment. Is there any additional information you can share with us?
 
  • #3
such as?
 

Related to Dickey Fuller Test Sine Wave or seasonallity

1. What is the Dickey Fuller Test?

The Dickey Fuller Test is a statistical test used to determine whether a time series data set is stationary or not. It is commonly used in econometrics and other fields to assess the presence of a unit root, which indicates a non-stationary time series.

2. How does the Dickey Fuller Test detect seasonality?

The Dickey Fuller Test can detect seasonality by analyzing the autocorrelation of a time series. If there is a strong correlation between the values of the time series at different time periods (e.g. monthly or quarterly), it indicates the presence of seasonality.

3. Can the Dickey Fuller Test be used to test for seasonality in a sine wave?

Yes, the Dickey Fuller Test can be used to test for seasonality in a sine wave. However, it is important to note that the test assumes a linear trend in the data, so if the sine wave is not linear, the results may not be accurate.

4. What is the difference between a stationary and non-stationary time series?

A stationary time series is one where the mean, variance, and autocorrelation do not change over time. This means that the data is consistent and predictable, and statistical tests can be applied to it. A non-stationary time series, on the other hand, has a changing mean, variance, or autocorrelation, making it difficult to analyze and predict.

5. Can the Dickey Fuller Test be used to test for seasonality in any type of data?

Yes, the Dickey Fuller Test can be used to test for seasonality in any type of data, as long as the data is time series data. This includes economic data, financial data, and even experimental data collected over time. However, it is important to keep in mind the assumptions and limitations of the test when interpreting the results.

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