Questions tagged [trend]

An observable pattern in the data.

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Cointegration and trend stationarity

Cointegration relationship is typically studied with integrated time series (that is, difference stationary time series) and when they have the same order of integration, it is possible that you find ...
Johannes Konrad's user avatar
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Is it correct to report R^2 value for simple time series trend analyses?

I am wondering if it makes sense to report an R^2 value for a simple trend analysis. For example, trends in temperature or stream flow over time. I understand that for linear regression R^2 makes ...
Mike Lavender's user avatar
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Is the link for a marginal trend in a logistic model the logit?

Exactly as in the title. If I estimate marginal trends for a logistic model, are these expressed as a log odds ratio? How does one express that in a way that makes intuitive sense? Change in odds ...
Bryan's user avatar
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Detrending and data transformation to logarithm can be done together?

I want to get the effect of bitcoin price changes on foreign currency price. The third variable is inflation, which is an explanatory variable. Should variables be detrended before regressing? Is it ...
user405402's user avatar
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Issue with coefficient estimate in linear trend regression model with autocorrelation of residuals

The question is simple, generally the coefficient estimate is not affected by autocorrelation of residuals when the independent and dependent variable are distinct. I am not sure about the clear ...
Sayooj's user avatar
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How to get rid of the time dependance?

I'm working with time-series and want to get rid of the time dependance, i.e. to get clean series (clean demand if one predicting user demand at some marketplace). Beginning with the classic paradigm $...
taciturno's user avatar
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Decomposition time series

I am studying a daily dataset from a game which contains informations about the peak of players from 2013-2023. This is my first try applying decomposition to see how time series components behaves. ...
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Determining the Appropriate Trendline and Statistical Test for Sleep and Muscle Mass Data

I am currently working on a dataset that explores the relationship between the amount of sleep (in hours) and the change in muscle mass (in kilograms). I have collected data and plotted it on a ...
Miles Jarra Gloekler's user avatar
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Can we interpret residuals in trend-seasonality decomposition?

General case: to build a model of market for further quality estimation of our algorithms. (Predicting optimal price, demand prediction etc.) Current approach: take two features of a product - price ...
taciturno's user avatar
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Is there a test for tendency when ANOVA is not significant?

I have a set of data that I think shows a slight decrease in the value, but there is no statistical difference among the groups. Is there a test to check if there is indeed a trend in the data in the ...
Gigiux's user avatar
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Different Joinpoint/Segmented regression results and Durbin-Watson test

I used the Joinpoint trend software (https://surveillance.cancer.gov/joinpoint/) and found interesting results to my data that really intrigued me. I have mortality rates from 2001 to 2021 as follows: ...
PosK's user avatar
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Forecasting Methods for a Short Time Series with No Trend or Seasonality in Python

I am pretty new into data science and I had some issues with my project. I am trying to build a forecasting model for a time series data. It is about yearly CO2 emissions from agriculture. The issue ...
HoriaC's user avatar
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Statistical test for a biology experiment when plants were grown in 3 different solution concentrations

I have conducted an experiment for my Biology Internal Assessment in the IB Diploma Course where I grew Phaseolus coccineus beans for 14 days. This is the overview of my experiment: Independent ...
Maja's user avatar
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Trending time-series and structural breaks

I am looking to find structural breaks in a time series, using the strucchange breakpoints function in R. I wonder whether I ...
IloveR's user avatar
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Counter-intuitive results from kpss test (Kwiatkowski–Phillips–Schmidt–Shin), on perfectly linear series

I would assume that a perfectly linear time series would exhibit trend-stationarity. This is not what I find when I use run this test in both Python and R. The KPSS test for stationarity around a ...
TunaFishLies's user avatar
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Role of `trend` argument compared to integral order in ARIMA model

I am currently studying ARIMA models. When I checked for a Python library to train one, I stumbled upon statsmodels which features ARIMA (and SARIMAX from which ...
Marco Bresson's user avatar
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3 answers
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How to measure change in growth rate between contiguous periods

I recently conducted a simple time-series analysis on some data. In this time series, we observe two elements (red and blue) that affect the trend during alternating periods. I want to measure how ...
gabriel's user avatar
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Why isn't Random walk with trend non-stationary according to ADF?

A random walk with trend doesn't have unit root. So, null hypothesis will be rejected. Hence, according to alternative hypothesis, since it doesn't have unit root, it will become stationary process as ...
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3 votes
3 answers
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How to visualize trends

I am working on a paper where we plotted BMI trends as a function of age in the population. We plotted trends for six databases, then we plotted for each sex, then for race, in three categories. I ...
Stefano Staurini's user avatar
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Mann Kendall test on raw time series or trend component?

I have about 20 years worth of monthly data tracking an indicator. My goal is to determine whether the indicator is going up or down over those 20 years. Mann Kendall tests seem like a good option ...
ryan_coogler's user avatar
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Cochran-Armitage trend test: variance of the T-statistic derivation

I’m trying to figure out the math behind the formula for the variance of the T-stat in Cochran-Armitage trend test show in Wikipedia. It says that decomposition is used, however I can’t work this out. ...
Ela's user avatar
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Repeated measures for ordinal categorical variable analysis in r

I have some environmental monitoring data that I've collected over 4 different years. I'd like to analyses the trend in the condition over this time period. 2010 2013 2017 2022 Very good 37 34 8 29 ...
Lannie84's user avatar
1 vote
1 answer
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ETS (error, trend, seasonal) formulation

Does someone know if there is (clever) way to formulate mathematically all the following models below: in a unique (system) of equations?
Vincent ISOZ's user avatar
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Why does adding a time trend can make an explanatory variable more significant in time series data?

So the statement is: Adding a time trend can make an explanatory variable more significant if the dependent and independent variables have different kinds of trends, but movement in the independent ...
Nol's user avatar
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How to deal with a Stationary DV and a Trend-Stationary IV in using OLS?

I have a dependent variable that is stationary in levels. However, one of the IVs is only trend-stationary (stationary around a deterministic trend that I can extract from the series). In other words, ...
user3672120's user avatar
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Difference between Trend and Level stationarity

In R KPSS test, what is meaning of level and trend stationarity? As far as I have read, trend stationarity means that once you remove the trend, the process becomes stationary. Is this the correct ...
Mohit Vijay's user avatar
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Significant Mann-Kendall but no Sen slope [duplicate]

I am doing trend analysis with Mann-Kendall and Sen's slope in R. I am getting a significant trend (tau = 0.242, p < 0.05), but when I calculate the slope I get 0 ± 0. Why is this happening? I have ...
Franchi's user avatar
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What statistical test to be used to find a change in the trend of a quarterly data with 20 data points?

Monetizable active Twitter users Quarterly data from 2017Q1 to 2022Q2 If I have to show that the trend was affected/increased in Q1'20, Which statistical test should I use? I expect to see the change ...
Nagarjun S's user avatar
1 vote
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What is the minimum number of data points/observations required to use Theil-Sen?

I am working on an algorithm which requires estimating trend magnitudes of data points. I have been told to use Theil-Sen as it is more robust to outliers and it is non-parametric. As users will be ...
locus's user avatar
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How can I back transform the residuals of a decomposed time series , where I used log(x+c) transformation on the original data?

I did a time series decomposition on a series of Twitter activity data into trend, seasonal and residual component. I checked the distribution of the residuals when fitting a linear model to the time ...
Mim_Tauch's user avatar
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R: emtrends pairwise contrast results change when testing slopes against 0 or 1

When performing post-hoc simple slope analysis on my linear mixed effect model in R using emtrends(), I noticed that pairwise slope comparisons showed differences in the significance when I tested all ...
Malin's user avatar
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Simulation data vs measure data

I am comparing climate simulation data (in reanalysis mode) to in situ measured data (from a weather station). For now, the main variable I study is snow height (in cm). Here is an exert of my data (...
Benjamin Imbach's user avatar
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Calculate price forecasts from forecasted returns

I have a question which makes me so hurt. Let's have a price time series $y_{t}$ for the same asset (for example, daily S&P 500 values) $y_{t}$ It can be trendy (trend stationary or difference ...
Dmitriy's user avatar
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Removing seasonality and trend for forecasting with tree based models

I am working on a problem where I'm using tree-based models (RFs, GBTs) for forecasting. I've read that I have to de-trend the data if I'm using a tree-based model, however, I am reading conflicting ...
harrynak's user avatar
1 vote
1 answer
56 views

Testing Trend Stationarity against Stationarity

I am trying to find a test where null hypothesis is that the series is trend stationary. I can assume that the trend is linear if that is going to help. So the series for null hypothesis is given by: $...
Bronsteinx's user avatar
1 vote
1 answer
51 views

Discrepancies in Mann-Kendall trend test results between different R packages

I'm experimenting with different R packages to calculate trends using the Mann-Kendall test. However, I'm getting varying results in terms of S, tau, and p-value. I would like to understand the ...
Yil's user avatar
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1 vote
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Test for existence of a linear trend in a time series

I want to know whether there is a time linear trend in a time series. What are some good approaches? One approach seems to test that the model belongs to ARMA(p,q) family however I am not sure if a ...
Bronsteinx's user avatar
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Anomaly Detection in Categorical Data

I want to build a system that will detect Anomaly for categorical data. I have a timeseries data like this For metric data these anomalies are calculated Outliers detection Trend Pattern Change I ...
Raj's user avatar
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Significance test for trend in time series with multiple sets of observations

Tomorrow there will be a race in which six runners participate in the 100 m dash. I will be able to capture the speed of each runner at each meter, so for each runner there will be a time series with ...
amd1972's user avatar
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Can We Use Mutual Information to Determine if a Time Series has a Difference Trend or a Time Trend?

Let's say we have a finite real-valued time series (finite subsequence of a realization of a real-valued stochastic process), $X_t$. To address my question, we make no initial stationarity assumptions....
QMath's user avatar
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Do I need to worry about trends in my time series model?

I am making a model of income for the pension system over 25 years. I have the income as dependent variable and number of workers and average salary as independent. Both income and salary are effected ...
Anfabei's user avatar
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1 answer
340 views

Trend variable in time series linear regression

tslm(Life_expectancy ~ Age + Gender + Race + trend, data=ts_df) Can I do something like this? I actually tried using this as a model and I got a different outcome ...
Priscilla Raj's user avatar
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Test for independence of trends

Suppose I have two distinct outcomes being tracked over time, A and B. An individual observation can have outcome A, outcome B, both (call it AB), or neither. If the rate of outcomes A and B are both ...
TY Lim's user avatar
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How choose Trend Specification in ARDL framework?

I am running ARDL model. For the model specification I have the following Trend Specification options: 1) None, 2) Restricted constant, 3) Constant, 4) Restricted Trend and 5) Constant & Trend. ...
Sane's user avatar
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0 answers
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How to continue analysis pipeline?

I have been working an a pipeline to analyze product parameters of a manufacturing process (e.g. different diameters, heights and color data) for quite a while now and it seems like I have hit a wall. ...
Krautsultan's user avatar
3 votes
1 answer
353 views

How do I present averages from different sample sizes across years?

I have 20 years' worth of observations that either say YES or NO to the question of whether breeding was observed. I want to present the averages of the YES observations across the years, ...
SamR's user avatar
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Gradient vs differences to remove non-stationarity in time series?

When dealing with non-stationary time series (for instance, in auto-correlation analysis), differencing (computing absolute differences between consecutive samples/observations) is often regarded as ...
joaocandre's user avatar
2 votes
0 answers
31 views

How to test for statistical independence on non-stationary time series?

I have multiple time series on which I want to identify statistically significant (if any) trends. To that end, I started by conducting the Augmented Dickey Fuller (ADF) test to identify which series ...
joaocandre's user avatar
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0 answers
137 views

Detrending these time series

I have the following time series. Its clearly not a simple linear trend. I want to explore the relationship among these variables using a VAR, or even a time-varying VAR. The biggest issue in my data ...
Marg's user avatar
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1 vote
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Hypothesis Test on Three proportional data with different sample size

I have three proportional data H1, H2, and H3. And my null hypothesis H0 would be H2-H1=H3-H2. What would be the test statistics here? I tried to use the proportional test for H_0:P2=P1. But the test ...
user15716547's user avatar

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