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Questions tagged [trend]

An observable pattern in the data.

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Adjusting VAR-coefficients for simulation

I am estimating a VAR-model, which I then use for Monte Carlo simulations. However, for some of the variables there is a clear downward trend in the data which we don't want to include in our ...
kraagje's user avatar
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3 votes
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What statistical test can I use? If any?

I'm currently investigating mortality rates in my local area compared to England. Mortality rates in my local area have always been higher than England however recently I've noticed a widening gap ...
Laura's user avatar
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Manual Calculation using STL Decomposition

Does anyone know how to manually perform calculations using STL Decomposition? I have this data: Date Count 2017-01-31 68 2017-02-28 59 2017-03-31 75 2017-04-30 71 2017-05-31 70 2017-06-30 68 ...
Devri Zefanya's user avatar
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time trend interaction

I have a panel dataset, and I want to perform some econometric analyses on it. I want to use a trend that interacts with the initial value of certain economic variables. For the trend, does it make ...
fernand's user avatar
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Investigating seasonality and trend in short time series

I am interested in investigating the presence, or lack of, seasonality or trend in very short time series (typically max 12 observations). Case in point: suppose one is looking at average number of ...
Astral's user avatar
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Seasonal_decomposition with no look ahead bias

I am forecasting the demand for a certain product. The demand dataframe contains a high trend component also some seasonality, for this I don't complicate much and use the method ...
Eduardo Contreras's user avatar
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Help with the result of a Mann-Kendall test

I'm testing the tendency of precipitation, with a data point per day, for many years. As you can imagine, the dataset oscillates wildly between days and many points are 0. I used ...
David's user avatar
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Should I control for unit-specific linear time trends in difference-in-differences

I have a staggered difference-in-differences setup and have been wondering whether I should be including group/unit-specific linear time trends in my model. It seems to be a common feature in the ...
Rob_research's user avatar
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How to aggregate the uncertainty around many predictions?

I have predicted trends for hundreds of time series. Each trend prediction comes with its own upper and lower bound at each time step. I would like to aggregate these trends and report them. Taking ...
Ress's user avatar
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54 views

Sales data trend

I have my historical sales data and I want to check for the trend (increase, decrease or no change). When I do my annual line graph, the slop of my linear equation is positive (indicating increase) ...
monique's user avatar
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2 votes
1 answer
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Interpretation of non significant results of the Mann-Kendall Trend Test

I am currently conducting a study on several climate datatsets, and am using the Mann-Kendall Trend Test to check if my Time Series Data contains monotonic (rising or falling) Temperature Trends. To ...
Sargnagel's user avatar
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1 answer
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Testing geometrical trend in a tail

I have a collection of values x1,x2,..., xm, ... xn, with n>>1. It has been observed that at 1<<m<n the points start following a geometric trend, i.e log(xi) -> linear. I need a ...
Jesús Castrejón's user avatar
1 vote
1 answer
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How do I determine sample size for determining a trend over time?

I want to characterize how batteries degrade over time. Due to the chemicals within the batteries, they naturally decay, resulting in batteries having less energy over the years. I want to figure out ...
Deepolisnoob's user avatar
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Appropriate Trend Analysis Test for Small Sample Size

Note: I have read Finding an appropriate trend test but unfortunately this post does not apply for me Suppose I have a small sample of data for 2 numeric variables $T$ and $Y$ where $T$ represents ...
NM_'s user avatar
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Is it possible to describe repeating data patterns as a stochastic process?

Generally, can repetitive patterns in sensor readings (e.g. temperature measurements at different locations over time) be seen as some kind of stochastic process? That is, if similar patterns repeat ...
joaocandre's user avatar
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Determine a robust trend from noisy time series data, when start and end years have a material effect

I have about 20 years of data, each year has a number of observations. If I put a linear trend through the data, I get a trend, and this trend differs based on the the choice of start and end year, ...
Mark Neal's user avatar
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Can I generate a time series with same features as a given dataset, but add a known linear trend coefficient (not just trend strength)?

I want to generate data that matches features of environmental data (that is often analysed with nonparametric tests due to nonrmality, skewness etc). I want to know how to best capture any linear ...
Justin Murphy's user avatar
1 vote
0 answers
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Quantile Regression Detrending

Assume I have a time series, as the black one below. As shown, the quantile regression for 5%, 25%, 50%, 75%, and 95% quantiles show different slopes (in red). Even if not quite visible, the ratio ...
Vincent's user avatar
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1 vote
1 answer
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Intercept or trend in a VAR model for stationary percentage changes [closed]

I am estimating a VAR model in R, using the vars package. There is an argument in VAR() function called ...
Alfonso's user avatar
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2 votes
0 answers
49 views

What to do in Box-Jenkins framework when time series has deterministic trend and seasonality?

I'm self-studying time series and I'm puzzled by apparent lack of consistency between : the "classical" decomposition of time-series and the Box-Jenkins methodology. Concerning the ...
Johannes Konrad's user avatar
2 votes
1 answer
108 views

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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0 votes
1 answer
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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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1 vote
0 answers
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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. ...
Racamposx's user avatar
1 vote
0 answers
39 views

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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58 views

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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1 vote
2 answers
688 views

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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2 votes
1 answer
77 views

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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1 vote
1 answer
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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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1 vote
1 answer
105 views

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
5 votes
1 answer
185 views

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
2 votes
3 answers
126 views

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
  • 93
-3 votes
2 answers
73 views

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 ...
catGPT's user avatar
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3 votes
3 answers
88 views

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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0 answers
25 views

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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0 answers
28 views

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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0 votes
2 answers
134 views

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
2 votes
1 answer
83 views

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
0 votes
2 answers
176 views

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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0 votes
1 answer
163 views

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
1 vote
0 answers
245 views

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
0 votes
0 answers
17 views

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
0 votes
2 answers
43 views

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
0 answers
97 views

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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0 votes
0 answers
36 views

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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