Questions tagged [trend]

An observable pattern in the data.

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Why do we detrend time series data?

If I have annual international trade (from 2000 to 2022) data and Country A has implemented a new policy in 2012. What is the benefit of detrending in this case if I want to investigate the impact of ...
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Can a timeseries with a clear trend be considered stationary?

I performed a augmented Dickey-Fuller test on a timeseries (that clearly has a trend) and, from the results, it suggests it is stationary (p-value = 0.01). Is this possible? ...
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P trend and association

what does p trend mean for categorical analyzes with HR (proportionnal regression cox) ? Do we have to interpret this with HR on our result ?
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Extracting the trend from the Gamm function in mgcv with a AR(2) correlation

I'm referencing a paper, "Filtering Time Series with Penalized Splines" from 2011 where the authors provide some code to show how a time series can be detrended by expressing penalized ...
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Nonpar group medians test with repeated subjects

Working with biomedical data, we have oddly distributed measurements, so we like to do nonparametric or medians tests like Mann-Whitney U. I would use wilcox.test() in R when comparing two groups. ...
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Creating custom trends or perform trend reversal in unobserved components model

I am using statsmodels unobserved components model to forecast some time series. I use the 'local linear trend' model, however I expect a reversal of trend at some point in the future. Is there a way ...
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Approach for Trend comparison in a Time Series

I'm a bit confused on how to properly compare a known trend to an estimated one. I've got two sets of data which are of the following format, $$y_{t_1}=x_{t_1}+WN$$ $$y_{t_2}=x_{t_1}+MA(2)$$ Where $WN ...
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trend between values in a single variable

What measure can one see to find trend between values in a single variable- for e.g if a gene is always overexpressed in different conditions. Other than skewness and kurtosis are there any other ...
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Testing for Trends in Sales Data, of 2 Products(Independent data of each Product)

The Data is structured as: Date of Sale | Order Amt | Price of product | Qty. Product A was sold independent of Product B(thus, 2 datasets), so dates do not match at certain instances, and entries are ...
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Contrary results using prewhitened MK test and MK test when checking significant trend of time series in R

I am testing whether the duration of drought (days of year) had increased significantly in the past decades. However, I am getting opppsite results using the prewhitening MK test and MK test in R. ...
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What is the formula for the p value of a tendline?

I can't find any no matter how hard I google. Every search result just tells me either how to calculate it on excel or explains what the p value is.
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How to measure strength of upward or downward trend in a time series

I have sales data of 500 different products from September 2021 to May 2022. I need to do a quick assessment on their time series characteristics. First of all I should name the ones which shows a ...
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How can I modify the mean absolute percentage error to account for the curve direction?

I am trying to predict the trend of a certain curve in the future (whether it will be increasing, decreasing, or remain constant). For evaluating my prediction, I am using the mean absolute percentage ...
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Should I difference my data before run a ADF test?

I plot my data as shown in the following screenshot: Clearly the series contains a trend. A first order difference of my data will eliminate the trend, which I plot as follows: Now I would like to ...
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Do we still have to care about stationarity when using a fixed effects model?

I have a balanced panel dataset for 37 countries and 11 years. I am using a fixed effects model for both country- and time-fixed effects. Now, I am asking myself if I still have to check stationarity ...
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How to check stationarity in panel data?

Unfortunately, I am not very familiar with panel data methods (yet) but it seems important to check if my data display stationarity (aka time trends). Assuming that my regression function looks like ...
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Where to start? [closed]

I am very new to data science and machine learning. I need some advice on how to recognize long/short-term patterns/trends in a big data set (demand data), make predictions for future and make optimal ...
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Testing for significant trend factors

I'm currently working on a project to improve my company's methods for frequency and severity trend selection in a few models. At the moment, given a series of points in time, we take a ...
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Seasonal and trend adjustment for irregularly spaced time series

I know of different methods that exist to remove seasonality and trend in the data to make it stationary. However, that exists only for regular time series; that is, a series that follows a fixed ...
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Handle User Behavior Change when creating a ML classifer

I'm creating a churn model. My first thought was that the bigger the training set, it would be better. However, 2020 was a crazy year because the COVID 19. For example, a user who was sick and ...
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How to generate a general trend from hundreds of time-series data

I have hundreds of time-series data from individual experiments[2] with a similar trend that reading rises as time goes by (evaluated by my naked eyes). So what statistical tools should I use to ...
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How to adjusting p-values from results of trend analysis on water quality data

I have results from Mann Kendall test for trends at 100 sample locations for 5 different analytes at each location (i.e., 500 p-values). If I had the trend results from 500 sample locations for 1 ...
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What are the best-practices for validating phone records? [closed]

I have a bunch of telephone data including information on call start time, end time, and duration. I am trying to evaluate the quality of the dataset to determine if the phone call data are legitimate ...
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How to compare trend of two different datasets?

I have two different datasets (ID 1 and 2) which show the number of animals per hectare for each year. I need to know if the trend for the first periode is different then the trend for the second ...
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Trend and Variance of Residuals for real world data

I am modeling the internal Resistance of a battery and have proposed the following equation: $$R_{int}(SOH,SOC,T,Current)=A_1+A_2*SOH+\frac{A_3*T*SOH*asinh(Current*\frac{SOC}{A_4})}{Current*SOC}+\frac{...
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How to compare trend for split datasets

I have product price data, at monthly frequency, available for a set of different products. Each of these series have a break point which is the point where we do some kind of intervention. The break ...
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VAR with trend-stationary variables

I'm currently trying to estimate a VAR with 3 variables - consumption, investment and a credit spread. I have inspected the variables and run ADF tests to determine that they are in-fact trend-...
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Mann-Kendall test for multiple groups

I'm currently working on a problem, where I want to test weather there is a trend in the course of a certain metric in an animal, where I wanted to use something like the Mann-Kendall test. The ...
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Which statistical tests can I conduct to analyse the trend of series data?

I have a dataset that measures students' time spent working on a set of mathematics questions. My dataframe looks a little something like this: Participant ID Question 1 Question 2 Question 3 1107 ...
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evaluate movement trend

I have some timestamped data (four groups) and I am looking to find a way to find which of the three is moving more closely with the purple one? Is Pearson correlation is the best approach, or there ...
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Which test or method can I use to assess trend in dependent proportions over time?

Let's assume there are 4 time points, t0 (baseline) ... t3 At each time point I assess a % of successes of some outcome: p0, p1...p3. The denominators vary over time, so the counts itself do not ...
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How to test for the increasing and decreasing trend in a non-time series data

I have the following data frame: ...
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Why does autocorrelation function for trend in data decrease with increasing lag?

Forecasting: Principles and Practice, 3rd edition by Hyndman and Athanasopoulos states in section 2.8, Autocorrelation that, for trend in data the autocorrelation function has positive values that ...
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Select the best period value to visualize clearly the Trend and Seasonality

I have a daily data for 4 years range between 2016 - 2019. I used statsmodels.tsa.seasonal.seasonal_decompose to decompose the seasonality and trend but I should ...
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How to deal with few trends in my time series?

I would like to make this data stationary, but I do not know how to deal with this series. This is not stationary and has autocorrelation. It looks like it has 3 different trends. How should I treat ...
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How do I test the significance of factors on a time series dependant data set?

I am working on a dataset where a new administrator joins a school, and I want to see if it affects the number of students at the school. There are also characteristics of the administrator (age, ...
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What is the mean and variance of an MA(4) process with time drift?

For a project I need to simulate a relatively smooth time series with an upward drift. This is what I came up with: $$y_t = \mu + \alpha t+ \sum_{j=0}^{q=4} \theta_{j} e_{t-j}$$ where $\theta_j = 0.2^{...
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Long-term trend prediction of time series data

I have a time series dataset project (single variable time series) on market share changes of a particular product in a region (values are recorded every day from 2018 to 2022) where I need to predict ...
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Testing Parallel Trends Assumption [duplicate]

I am applying a difference in difference method to a time series with daily [365] observations in both the treated and control groups. To test for parallel trends I was planning on just undertaking a ...
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Is there a way to do adjustment for several baseline variables for the Cochran Armitage test?

I have a dataset in which I look at the relationship between blood pressure status (a categorical, dichotomous, non-ordinal variable of hypertension and normotension) and glycaemic status (a ...
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Exponential trend stationarity in GDP time series

My economic textbook assumes that Gross Domestic Product is characterized by stationary deviations from a constant growth rate, reporting the following equation: $Y_t = Y_0(1+g)^t \exp(u_t)$, where $...
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3 votes
1 answer
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Live peak / trough detection (data provided)

At the bottom of this question is the data of three time series in CSV-format. All are of same length and they all contain measurements of the same event "A". But each time series is using a ...
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Accounting for trends in experiments

At my work, we have this algorithm of sorts, called 'Mean 2.0' for analyzing experiment results. The idea is that your data is divided into four buckets by the partitions, pre vs post experiment start ...
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Time series rejects the null hypothesis for ADF test with drift no trend. Is the time series stationary? Must I differentiate?

TL;DR: My time series passes a ADF test with drift no trend. So, should I leave my data alone and proceed? Or do still need to differentiate it before modelling, because it has drift? Or have I made ...
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2 votes
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Significant Mann-Kendall trend but Sen slope = 0?

I used the Mann Kendall trend test to determine the significance of the trends of the following time series data (sheet 1) and obtained a significant trend at 10% significance level for the month of ...
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Calculating trend for an array of numbers

I have a website on golf statistics and wanted to calculate the trend for various things. E.g. for fairways hit off the tee, let's say I have values = ...
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Does a constant term in a nonstationary AR model always imply a trend?

Given an $AR(k)$ model of the form $$y_t = \alpha_1y_{t-1}+...+\alpha_ky_{t-k} + \mu + \varepsilon_t$$ with $\alpha$ satisfying $(1-\alpha_1 z - ... -\alpha_k z^k ) = 0$ for $z=1$, does a nonzero $\mu$...
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Choosing between First-Differences and Fixed Effects (Within estimator) - arguments in favour of FD

First of all, I'd like to say I have read the standard econometric textbook sections on FE vs FD.  Therefore, I am familiar with the relative efficiency of each of the methods depending on the ...
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how to quantify the strength of trend in univariate time series data?

I have data that looks something like this: ...
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Interpreting ACF and PACF for data which have had its seasonality removed

I'm currently working on a project and trying to figure out how to interpret my ACF and PACF plots. I have removed seasonality from the data in order to establish the trend, now when plotting my ACF ...
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