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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Stationarity in an interrupted time series
I am using proc autoreg in SAS to conduct an ITS analysis and I have a question about stationarity. Proc autoreg is able to ...
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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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Using KPSS test in Python with statsmodels
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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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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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Order of integration for a time series with constant mean and increasing variance
I am trying to find the order of integration of a time series. I checked for stationarity using the ADF and KPSS tests. Both the tests indicated non-stationarity, so I differenced the series once and ...
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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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Testing by using KPSS
When use KPSS to test the stationarity of data series I get this warning .Does it affect the final results?
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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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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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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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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 Test and KPSS Test contradicting, differencing wont make the time series stationary
My time series is on Life expectancy at birth from 1960 to 2018. Obviously, it has an increasing trend and ACF also supports this because the ACF values dampen so slowly. However, ADF test p-value is ...
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KPSS test: p-value greater than 0.05 but test statistic is less than critical values
I am using Python Statsmodels to find out if my time series is stationary or not. My time series (after the first level shift) passed the ADF test and it suggested that the time series is stationary. ...
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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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Evaluating the importance of a unit-root
I have a monthly time series and I'm trying to determine if such set of data is stationary or not; the dataset is about composed by 160 record.
Specifically, I'm running 2 test found in literature:
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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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Can adf test and kpss test contradict?
I have a time series data for 18 months.
To check for stationary I conducted adf test, to which my p value is 0.8.
And kpss test has a p value of 0.1 , so at 95% confidence level I fail to reject null ...
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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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Is my Data stationary? KPSS, ADF Tests and ACF
I already differenced my Data by 1 and i am not sure whether my Data is now stationary or not. I perfomed an KPSS and ADF test in order to help me decide if it is. I think it is stationary but im not ...
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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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differencing in sARIMA models
Im currently trying to fit unemployment data to a sARIMA model. Unemployment has usual yearly seasonal trends so a seasonal difference is given. Log transformation is applied to minimize the errors
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How to check if a process has constant variance?
I am using KPSS test to verify if my process has constant variance around the mean, but I am not sure if this is the correct test for my case. In KPSS the null hypothesis is that the process is ...
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What does my ACF test tell me about numbers to use in ARMA?
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I want to use an ARMA model for seasonally adjusted quarterly GDP growth figures and then check for structural breaks. I've run an ACF, PACF, kpss and adf test on the data I have, and you can ...
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How to interpret KPSS test
I have been trying to understand the kpss test and I have read this answer and have been reading information from this KPSS Test: Definition and Interpretation , but am still confused about my own ...
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Confused on kpss.test shows both "Trend" and "Level" are smaller than p-value R
I am fairly new to time series analysis. I am using hourly data for six months time period. My time series has seasonality every week. Per Dr.Robert Hyndman
I set up my time series variable and then ...
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How do I tell that my time series is stationary or not?
I am new to time series analysis and I am trying to model a time series.
I know there are similar questions but I could not figure out the solution to my problem.
I have a time series like the one ...
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Stationarity tests in a regression model [closed]
In a model I am trying to justify, a mortgage rate spread is estimated by regression on a swap spread using around 40 monthly data-points. The model fails the assumptions of heteroskedasticity and ...
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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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Bounded dependent variable: can it be unit-root non-stationary?
I have linear time series regression model where the dependent variable Y is bounded between 0 and 1.
Using classical unit root tests (dickey-fuller and kpss), results would make you conclude that Y ...
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Matlab - kpsstest
If I have:
a=randn(100,1)
[h,p] = kpsstest(a,'lags',0:10)
why does the test fail to reject the nonstationarity hypothesis?
It gives back ...
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Contradictory results of ADF and KPSS unit root tests
To check whether the data is stationary or not, I computed KPSS and ADF test and got the following results
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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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Seasonal data deemed stationary by ADF and KPSS tests
I have got two time series and I want to evaluate a VAR model. For this, it is necessary that both time series are stationary.
Using R, I have found periodicity ...
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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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R: Box.test vs adf.test vs kpss.test
I stuck in checking my Time Seies for stationarity with several tests:
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Fractional Gaussian noise, the KPSS test, and stationarity
Fractional Gaussian noise (fGn) is characterized by the mean ($\mu$), the standard deviation ($\sigma$), and the Hurst index ($H$). It's my understanding that it is stationary, for the simple reason ...
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Unit root tests ambiguous - is time series stationary?
I am testing a time series (quarterly) for stationarity. However, using the KPSS test, the ADF test and PP test, I get different results (ADF and PP reject non-stationarity, KPSS rejects stationarity, ...
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How can this time series be stationary?
I have the following irregularly spaced time series.
The related autocorrelogram is:
and I run the following tests:
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kpss test in eviews
I am taking 5% critical values for adf pp and za. In kpss test critical value is passing from 1% but not from 5% so
is it stationary or not also when take differences of series first and second ...
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Interpretation of ADF(Augmented Dickey-Fuller) and KPSS (Kwiatkowski–Phillips–Schmidt–Shin) tests for time series
Can anyone please clarify for me the differences between ADF (Augmented Dickey-Fuller) and KPSS (Kwiatkowski–Phillips–Schmidt–Shin) tests in testing the stationarity of a time series?
I tested my ...
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