Questions tagged [change-point]
Methods that attempt to detect when a change occurs in a distribution, process, or function.
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Bayesian change detection (sampling the posterior of a Poisson distribution)
I'm trying to work out how the posterior of a Poisson distribution is derived to enable me to detect changepoints. I'm trying to follow the example here.
$Y_i$ (events per year) is modelled using two ...
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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 ...
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Before-after intervention variation: difference in-difference or broken-stick regression?
I am trying to figure out which analysis would best answer our research question.
Our study aimed to find out whether the variation in surgical rate decreases in a group of hospitals after an ...
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How to forecast changepoints from Gas Concentration Data?
So I'm trying to predict when gas concentrations change from sensor conductivity readings over a day. The gases randomly change concentrations around every 80-120 seconds and are kept constant between ...
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Is new value coming from the distribution of the previous points?
I have a set of 30 data points, measuring percent of acknowledgement of an event that should not happen. So ideal value is 0.0 but we are getting some values greater than that, of order $10^{-5}$. It ...
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DCC as a model of dynamic conditional autocorrelation?
Is it a good idea to use DCC to estimate dynamic conditional autocorrelation? So far I was using the indirect method for detecting changes in autocorrelation - in R strucchange package by Score-CUSUM ...
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Change Points in Cox Model
I have trained a Cox model on my dataset, which comprises patients entering the study at various time points. I suspect there might be multiple change points indicating shifting effects over time. My ...
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How to detect moments of state change in boolean time series?
Let $A = (X_1, ... X_n)$ be a series consisting of long periods of ones interrupted with shorter periods of zeros, like
$$A = 111111111 00000001111111111100000011111111111111.$$
The plot below (left) ...
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Are there tests on parameter stability for time series rolling OLS?
I have an OLS model implemented in a rolling window scheme. The estimated params $\beta$ do change for each window, and the entire intention is to capture any structural change, but they should not be ...
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How to handle recent variable change resulting in level-switch in time series modeling?
I developed a script to run time series models on people data, and I re-run the Arima model fitting/forecast reconciliation algorithm monthly as new data comes in. I use the grouped/hierarchical time ...
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Best Approach to Detecting Breakpoints in Continuous Treatment-Outcome Relationship?
I am currently conducting research to understand the relationship between a continuous treatment variable and a continuous outcome variable. To mitigate confounding and selection bias, I am employing ...
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Assumptions in Changepoint analysis (EnvCpt) of Time Series
I'm looking to identify changepoints in my time series data. To begin, I've seasonally adjusted the data using JDemetra+. Next, I'll carry out a changepoint analysis utilizing the EnvCpt function in R....
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Efficient method to detect large probability shifts in HMM model output
I am using an HMM model, the specifics of which I cannot disclose. However, my objective is to detect significant transitions in the model's output probability distribution. This probability ...
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Finding the threshold at which events become significantly more frequent
I have two sequences of data: air temperature T and event A. High temperatures can cause Event A, or it can just happen randomly (or other reasons). In the database, some events A are attributed to ...
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Structural breaks in Survival Analysis
I am currently conducting research using panel data to analyze survival patterns. This involves examining the time-to-event data of a diverse group of participants over multiple years, where the ...
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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 ...
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R, structural change and Wald test
I'm doing a time series analysis and wanna identify structural breaks from a regression. Here are the data: https://raw.githubusercontent.com/ramyshaban01/dataframe/...
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How to determine if change in time series is noise or significant?
I am looking at weekly sales data and see that sales last week dropped by x%. I see that weekly sales do fluctuate quite a bit so not sure if this is indeed a problem. What statistical methods can I ...
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Changepoint detection and forecasting
I am seeking to develop a three-staged algorithm that should be able to detect change in
Mean
Variance
Both Mean and Variance simultaneously if they exist.
I would be glad if this program can also ...
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Period cutoff in Chow test
I am using the Chow test to analyze structural change in time series data potentially caused by a significant event. Since each data point represents a day, the data is broken into two chunks:
Chunk 1:...
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How to test if the mean of a time series has significantly shifted at a certain point?
sorry if this has been asked before but I have searched the internet a lot but have not been able to find a satisfactory answer.
I have a time series (approximately 25 points) and I have implemented ...
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Detecting Events in a series
I have a series (sensor readings) with different events and I'm trying to segment/detect those events for further analysis using change point detection in python.
In general, the series consists of a ...
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What is a reasonable range of penalty values to try in PELT changepoint analysis?
I have a simulated a time series data set several predictor variables and response class that I created to practice different analytical techniques before I apply methods to my real (very large) ...
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What should I do with structural breaks at return time series?- R
Let say I have the below time series data(It is a return data of a financial derivative):
...
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Structural break near the end of training sample
I have multivariate time series (VAR), and i found a break near the end (84.7%).
I wanted to use a dummy variable in this situation, but even if I choose 90% training set, the dummy only trains on 100 ...
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Finding patterns of volume worked - Productivity Mix Correlation
I am trying to generate labor standards (the amount of productivity per hour an employee should be accomplishing) based off of historical data volumes. I do not have the start and end time that a ...
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Check exponential smoothing forecasts for significant changes
Suppose I have a time series that I model with double exponential smoothing as implemented in the R package forecast via the ets ...
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change point detection of time series
Currently, I am working on a research project that involves forecasting electricity consumption using data mining. In my analysis, I have detected the change point for time series using the ...
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Change point detection for trends (as opposed to outliers)
I'm reviewing literature of change point detection, and if I understand the concepts, this methodology would identify various points that don't belong (outliers, anomalies, etc.)
However, I'm very ...
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How to interpret a positive effect of a predictor on a latent change score with a negative slope?
I have SEM model in which M mediates the relationship between X and Y (i.e., X predicts M; M predicts Y). Further M is a latent change score, calculated by regressing observed scores from time 1 and ...
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Is it reasonable to choose a subset of the time series to create a model?
I am new to time series forecasting and would much appreciate your reply. I have an annual housing starts data between1970-2022 shown, below.
I want to forecast the next 10 year housing units. If I ...
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Determine what is the break point for the slope change in R [duplicate]
I am trying to create a plot with 2 linear regression lines for each group (i.e., CAD, and Healthy). One linear regression line ...
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How to efficiently fit a spline with a linear piece between two constant pieces
I have two dimensional data, to which I'd like to fit a spline function.
A spline would be defined as this:
y_0 for x<=...
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How to deal with VECM with a different structural break for each time series?
I am modelling a VECM with structural breaks. I am following Joyeux (2007) way of doing it with dummy variables, including the different trace and eigenvalue stats for cointegration with structural ...
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Identification of a significant change in slope (trend) in noisy and scarce data sets
I'm working on a problem where I need to find a significant change in slope (trend) in noisy and scarce data sets.
Below are some examples of the data sets I’m working with to showcase what I mean by “...
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F1 score for change point detection
I'm trying to evaluate my change point detection algorithm based on F1 score[1] defined as follows
Let $\mathcal{X}$ denote the set of change point locations provided by a detection algorithm and let $...
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algorithm to either fit data as linear or stepwise constant
Given data $(y_i, x_i)_{i=1}^n$, I wish to fit either:
a linear regression, $y = \beta_0 + \beta_1 x$; or
a stepwise constant function, $y = \left\{
\begin{align}
y_1 & \text{ if } x &...
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Poisson Model Interrupted Time Series Analysis
I've run an Interrupted Time Series Analysis on count data, fitting a Poisson Model as below:
...
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From which X value, Y starts to be different?
Here are data about the ventilation response (VE) to exercise (i.e., increase in oxygen consumption or VO2). In normal condition, ventilation increases linearly until a threshold where ...
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Weird results regarding structural break test in R
So I downloaded stock data and differenced it to get log returns. Im trying to split my dataset in a pre-covid and covid period so I try to detect my dataset for structural breaks. I fitted the ...
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Finding significant differences between slopes
I have a graph showing a continuous variable plotted against a discrete variable:
I'm looking to identify the point of diminishing returns or the point at which the slopes from two points on the x-...
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How to prove statistically that mean jumps when a parameter crosses an unknown threshold value?
We have a random numbers generator (it is actually a physical device standing outside of our building). By collecting of about 3000 numbers, generated by the device, we came to the conclusion that the ...
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Structural Changes - Utilizing R-package strucchange to Test for 0 vs. l or l vs l+1 breaks
I'm using the R-package strucchange (https://cran.r-project.org/web/packages/strucchange/strucchange.pdf) to test for structural changes in different time series.
...
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Is there a way to tell when a time-series can no longer be predicted by the same model?
I am modeling a time series using a multiple (dynamic) linear regression model. I suspect that at some point, the model no longer accurately predicts the true series. Is there a way to find the point ...
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How to perform a breakpoint analysis on these two variables (Survey Score and Total # of Outages)?
Here is a snippet of the data:
I believe both of these are discrete variables. I want to first determine if a correlation exists. Would I utilize Kendall’s Rank Correlation? Second, I want to create ...
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Estimating stationarity of evolving distribution
Consider a probability distribution $P_t$ at time $t \in \mathbb{N}$ which evolves in time, but is assumed to become stationary at some unknown time $t_0$, i.e $P_{t_0+1} = P_{t_0}$
To make matters ...
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Chow F statistics using strucchange for ARMA(1,1)
I am looking to generate a series of Chow F statistics for an inflation rate series. I am using the strucchange package. Specifically, the Fstats() function. I want to calculate the Chow F statistics ...
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Identifying concept drift in the presence of data drift
Usually concept drift is defined as a change in the conditional distribution of our target variable with our covariates,
$P_{0}(Y|X) \neq P_{t}(Y|X)$. It is also known as real concept drift or ...
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Changepoints in linear regression (NOT piecewise regression)
I have two variables, X and Y, whose relationship can be described well by a linear regression. HOWEVER, this relationship changes every once in a while. It is not that the relationship changes ...
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Prophet not fitting data correctly
I'm currently looking to build a time-series model to do change point detection on a churn dataset, in order to check that the covid19 measures taken during the pandemic had an influence on churn.
I'm ...
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