Questions tagged [kpss-test]
Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test is used to analyze time series. The null hypothesis is that the time series is stationary. It is often used to complement an Augmented Dickey Fuller (ADF) test.
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The contradiction in KPSS and HEGY test
I am new to this field and I have a question.
I have a seasonal rainfall dataset and I want to apply SARIMA model on it.
For this purpose, I applied the KPSS tests and I got the following output:
<...
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ADF and KPSS test both rejected
When testing the stationarity of residuals after OLS estimation, the ADF and KPSS test have opposing conclusions when it comes to rejecting the null:
ADF: Rejection of null concludes evidence of ...
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Time series and stationarity tests
I perform some time series fitting with the help of the forecast and urca packages. I have a question regarding the corespondance between results coming from ...
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About 2 unit root tests and null hypothesis
I have been looking at unit root testing. Specifically 2 tests:
The ADF test.
The ADF (augmented Dickey Fuller) test has the null hypothesis that "the time series has a unit root" (meaning that the ...
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Practical time series advice
I have collected performance data at fixed time intervals from a 'shared system' with the aim of investigating the affect of the sharing on the performance of my 'slice' of the system. The performance ...
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How is it possible that the statsmodels KPSS test rejects trend-stationarity but not stationarity?
take the time series in the code block below - if I run a KPSS test using statsmodels based on a regression around a constant (i.e. test for regular stationarity), ...
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Test to show that the underlying process of two non-stationary time-series are different?
Let's say I have carried out two experiments where something was changed in one compared to the other. I measure a feature in each experiment and therefore have the two time series for this feature, ...
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Kwiatkowski–Phillips–Schmidt–Shin (KPSS) and Augmented Dickey–Fuller (ADF) Tests
I have been searching for a sample usage of the KPSS and ADF tests, however I can only find pages reporting examples using R or Python. The mathematical definition of the KPSS test also seems to be ...
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How to assess stationarity when kpss and dickey-fuller test give conflicting results?
I have used R to test the residuals of my time series data, I have used the tseries function for the kpss and dickey fuller test. Both gave conflicting results where dickey fuller said the data was ...
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Time series regressions
I'm trying to make a basic scatter plot/regression to look at the relationship between two time series. Series a is volume of mentions of a product on a forum over time, series b is the sales of the ...
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Is my interpretation of ADF and KPSS correct?
I am new to time series analysis, and I am trying to interpret the ADF and KPSS results. Is my interpretation of stationary correct?
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KPSS: Difference between level stationary and trend stationary
Can anyone please clarify for me the differences between level stationary and trend stationary in KPSS test? I run the KPSS test with trend and level on same time series and the results are:
H0: ...
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KPSS test & ADF test - range to choose for lags
Suppose I want to check if a series is stationary with the KPPS test;
the literature suggests to take as lags $\sqrt n$ where $n$ is the number of observations. Do you agree with the literature?
Which ...
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Contradiction in the ADF (Augmented Dickey-Fuller) and KPSS (Kwiatkowski–Phillips–Schmidt–Shin) tests for financial time series
I use the ADF and KPSS to test for stationarity / non-stationarity of price increments in financial time series.
The two test applied provide different results for low lags, but the same result for ...
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Johansen Cointegration Test returns non-stationary error even though trace statistics suggest their existence
Before I start, I asked this question on Quant Finance before. But other Questions going into the same direction have been redirected to this stack exchange. Therefore I post this here as well.
I'm ...
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Is it valid to perform a stationarity test on a single frequency of a time-frequency spectrum?
Am I violating any assumptions if I perform a test such as the KPSS test on a single frequency band of a time-frequency spectrum?
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ADF and KPSS test both conclude stationarity but the time series has trend?
I am trying to implement time series stationarity tests on my data. When I carry out ADF (Augmented Dickey-Fuller) and KPSS tests on my data the p values suggest time series stationarity. However, ...
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KPSS test and ADF test
I have 10 datasets and I tested all these dataset by using ADF test and I get on p-value = 0 (p-value<0.05 this mean the series is stationary) .
After that I used KPSS test and I get some dataset ...
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Stationarity of time series with KPSS test
I have dataset with size 4630 and I used KPSS test to check if it is stationary or not. I get on this output, Is that mean the value of p_value is not correct? or how can test large values with kpss ...
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Cointegration between 2 Stocks. - confirming Times Series Stationarity using ADF & KPSS Test
I had created a google sheet with the help of online resources, - to conduct cointegration test on 2 stocks time series. It checks null hypothesis, to see that a unit root is present on the residual ...
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determine if series is non-stationary or stationery
I have series and I need to determine if the series is stationary or non-stationary. According to this web page Link, is prefer to use the ADF and KPSS and then judge on the series. My result of ADF ...
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Stationary in levels I(0), three variables -- cointegration test?
After running ADF-tests and kpss-test I find that the variables are stationary without drift and trend. I have two questions:
Is it the correct use of terminology to say that they are not integrated, ...
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What to do when kpss contradicts ADF?
I'm testing to see if Inflation has a unit root and if it has a drift and trend, just drift or no drift and trend. My results from the ADF test looks like this:
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KPSS test and heteroscedasticity
I am trying to transform a time series to make it stationary. After two differencings it looks like this:
KPSS test value is 0.01075801 with p-value=0.1, so the stationarity is not rejected. But just ...
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kpss test always gives a very low P value
I have tried to use kpss.test() function in R, but it's output confused me a lot. So I tried the below code:
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Can a ratio variable be trend stationary?
Can a ratio variable, e.g. the wage share of factor incomes, really be trend stationary? It is bounded between 0 and 1 and moves in between during long periods, acting like a non-stationary variable. ...
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