Questions tagged [change-point]
Methods that attempt to detect when a change occurs in a distribution, process, or function.
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24 views
Guidance on time-series change point detection or identification of contributions
Let me preface this by saying that I am not a data scientist. Please excuse any imprecision in my use of subject specific terms or notations. Please feel free to edit my question, to improve any ...
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2answers
100 views
Time series analysis with recurring event (python)
I Have a vector of n values and I have event that occurs occasionally throughout this vector.
So I have
V1 = [300, 120, 450, 700, 880, 400, 100, 60, 44, 91]
...
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0answers
30 views
How to estimate changepoint from Cox survival model with time-varying effects?
I'm wondering the best way to model the duration of time to a changepoint in survival within a known-fate, continuous time survival model (as well as estimate survival rate before and after the ...
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1answer
24 views
Pearson correlation in data set with “jump”
I'm trying to calculate the correlation between the condition number of a finite elements matrix and the coarseness of the mesh that it represents.
However, when trying to calculate the Pearson ...
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0answers
21 views
Construct Confidence Curve in R in Change Point analysis
I am trying to reproduce the journal article "Confidence distributions for change-points and regime shifts" (on page 16 top left hand corner)
Firstly, I generated random sample using i) N(1,1) and ii)...
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0answers
38 views
regression change point model
I am novice at best with linear regression models and I am interested to learn how to do a change point model in Python if possible. The data that I analyze is a years worth of electrical energy (kWh) ...
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2answers
45 views
Detecting change in p of a Bernoulli process
A machine outputs either a 0 or a 1 each second. We denote this output at time $t$ as $b_t$. The probability that it outputs 1 is $p_t$ at time $t$. How do we go about studying the change in $p_t$ in $...
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1answer
41 views
How to statistically determine if there was sales lift?
Say my company is about to make some changes that they expect will increase sales and customer acquisition in current markets, what would be the best way statistically to determine if that lift was ...
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0answers
20 views
Measuring the effect of an outside force on time series with trend and seasonality
Let's say I have a time series that shows daily traffic to my website. My website is getting more popular so there's a trend up, and the traffic is based on day of week so it's cyclical with a period ...
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0answers
34 views
How to find the timepoint when on average each timeseries reaches a given threshold with hypothesis testing?
I have N individual timeseries and would like test statistically - after the fact - when they cross a given threshold - specifically when they are reliably above 0. I am new to timeseries analysis and ...
2
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1answer
125 views
Pettitt's Test for Change-Point Detection Showing P-Value Larger than 1
I am studying how to use the pettitt.test function from the trend package in R to detect change-point in a time-series. However, ...
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1answer
479 views
Changepoint/Step Detection in Univariate Time Series
As a beginner to time series analysis, I'm trying to understand the best way of detecting the points at which my univariate time series shows a change in trend direction (see highlighted example).
I ...
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151 views
CUSUM algorithm and first derivative
I have a doubt about implementation of CUSUM algorithm. I found a Python implementation here.
It is based on a formulation of the CUSUM that basically tracks positive ($g^+$) as well as negative ($g^...
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1answer
119 views
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1answer
85 views
Hierarchical Version of Bayesian Change Detection Model in JAGS
I am trying to create a hierarchical changepoint detection model in JAGS, estimating group difference in changepoint based on individual changepoints in scores for an outcome variable (fictional in ...
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2answers
71 views
R changepoint, different number of outputs
I tried detect change points in R. I've ran following MWE in R.
...
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1answer
58 views
Finding statistically significant changes in a time series
What would be the proper way to determine statistically significant changes between time periods within a time series (between Yn and Yn+1)? I thought about taking the first difference and ...
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0answers
30 views
plotting the regression lines in each iteration (chngpt package) [closed]
I want to plot the regression lines for each iterations of the chngpt package. Link to chngpt package
Here's my sample data:
...
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0answers
298 views
Change detection point with python
How reliable is using KS test (https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.ks_2samp.html) for change-point detection (in a single vector)?
Is there a better way for this, in ...
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0answers
30 views
Time series clustering/segmentation based on pattern
I'm currently working with a database which contains several large PPG (pulse oximetry) and ECG time series. These series, however, contain segments within them which are highly contaminated by noise, ...
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0answers
30 views
Finding the likelihood of a normal distribution in a change point model
The simple change-point problem can be described as follows. Here it is assumed that both $p_1(y)$ and $p_2(y)$ are known completely.
$y_1,...,y_\tau|\tau $ are iid with distribution $p_1(y)$ and $y_{...
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0answers
245 views
Edge detection in time series
I have a time series (data here) which contains several square-wave jumps, as well as some physical signals of interest. An example is shown in the top panel of the figure below. There are square wave ...
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0answers
25 views
On the use of running total instead of raw data in change point detection
I am working with a percentage time series data recorded at irregular time step that generally shows or expected to show a decreasing trend with time (and at an increasing rate towards end of the time ...
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0answers
35 views
Understanding a cost function
I have been analyzing a cost function used in a point of change algorithm.
I am having trouble understanding the notion of a cost function and how it generates results for example.
...
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0answers
47 views
Find a “drop” in continuous time-series data
I have a dataset of a lot of time-series data of single observations. I am looking for a way to find a specific pattern in this data. As seen in the figure, the data does not change much over time, ...
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35 views
Hypothesis testing on dependent samples to identify change point
I want to perform hypothesis tests on the correlated observations. Practically speaking, suppose there is a sequence of data points $X_n$, which could be regarded as the observations from a certain ...
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0answers
34 views
How to estimate point of jump in a regression model?
So non-parametrically it is observed that once the temperature hits approximately 300K, there is a jump in conductivity of a material. Now the estimate is noisy and seems to shift slightly based on ...
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1answer
122 views
Finding changepoints in the movement of a car with respect to a lead car (using ecp package in R)
Main Question:
How do I apply e.divisive method from ecp package effectively on multivariate time-series, so that the resulting ...
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1answer
231 views
Need advice on change point (step) detection
I have a time series with lots of steps/jumps (data file here). A plot is given below. I would like to subtract an appropriate value for each of these square wave features to bring them back down to ...
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1answer
82 views
Detecting changes in large number of time-series that share seasonality
I have large number of time-series that are independent of each other, but share some seasonality patterns. I need to detect anomalies/changes (increased volume, change in mean), that appear in the ...
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1answer
52 views
sequences of different length
I have two sequences of coin tosses, which have different lengths. I want to compare their likelihoods under a model. But since the likelihood is a product of probabilities, the longer sequence ends ...
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1answer
36 views
Bayesian Information Criterion - Non-physical model selection
Following the work of Bai & Perron (1998) and others in detecting structural changes in time series, I am trying to select the breakpoints by using the Bayesian Information Criterion.
Basically, ...
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2answers
45 views
Demonstrate change of predictor variable for a time series [duplicate]
I have the following problem:
Assume there are three time series $h(t)$, $g(t)$ and $f(t)$.
The hypothesis is that prior to $t_1$: $h(t)=a\cdot f(t-t_2)$
and after $t_1$: $h(t)=b \cdot g(t-t_3)$.
...
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0answers
54 views
Is it possible to use statistics to detect a rising temperature scenario?
It is required to monitor temperature data from a manufacturing environment. The particular use case is to detect if the temperature is rising beyond normal values to enable timely corrective action. ...
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1answer
399 views
Identify two major change points in time series data and summarise for several replicates in R
I'm working with temporal simulations (forward in time) and I would like to find the best way to detect the two major change points in this time series.
I have several replicates of the same ...
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1answer
99 views
How do I do a change point analysis on a sparse data set in python?
So, I have some data from video game playtests, where players were allowed to play a game at home for a week, and were asked to fill out a daily survey. In particular, they were asked to rate a ...
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1answer
48 views
Time series random chance detection
I have a time series data of monthly sales for the last 4 years. The sales for one month eg Feb 2017 is much higher same month last year or the last month sales of Jan 2017.
If i wanted to detect if ...
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0answers
57 views
How to statistically demonstrate a change of the predictor variable to a responding variable from time t on (time series)?
I have the following question:
I have three time series. Two form possible predictors (f(x) and g(x)) and a third is the responding function (h(x)). f(x) and g(x) exhibit different lags to h(x). Now I ...
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0answers
33 views
What type of model can be used to detect changes in periodic behavior?
Imagine we have a data sequence centered around 0 with small fluctuations +/- 1, but approximately every 100 observations it jumps to 10.
If this behavior changed and it started jumping to 5 every 50 ...
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2answers
4k views
Time series anomaly detection
I am tasked to develop an anomaly detection system for data organised in many 1D (can be more than 1D if I choose, but I think that will complicate the problem even more) daily time series. The series ...
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4answers
1k views
Anchoring a linear regression to a specific data point in r
This is different, follow up question to someone else's question here:
I am very new to R and have no programming experience what so ever but I am holding my own for the data analysis we need in my ...
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0answers
98 views
Changepoint detection in a single unevenly spaced time series
I have a single time series, unevenly spaced. I would like to perform change point detection on it. Does it mean a non-parametric method is needed? Any pointers to which method would be valid? Also, ...
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0answers
158 views
How to detect distribution changes within population?
I have a time series data of populations, e.g. for each time point, I have the blood pressure of 1 million of rats. How can I monitor that the distribution of this population drift over time?
For ...
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1answer
190 views
When testing for structural changes, should a linear trend be identified from the data or the derivative of data?
There exists a linear trend in an otherwise non-linear set of time-series data. The linear trend can be identified using a change-point (or breakpoint for structural changes) analysis method. This ...
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0answers
136 views
detecting change point in the time series on a 2 dimensional space
I have a 2 dimensional geographic space. There are crime events occuring at different regions in the space over time. I am looking particularly at property crimes like burglary. If I look at the time ...
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2answers
113 views
How do I split a vector and minimize absolute error efficiently?
I have a vector $y\in\mathbb{R}^n$. I want to find a computationally efficient way to find a split point $k$, such that:
$\sum_1^k |y_i-\theta_1|+\sum_{k+1}^n |y_i-\theta_2|$ is minimised. The $\...
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3answers
317 views
Forecast time series with breakpoint using Holt-Winters (R)
I have a time series dataset for forecast using Holt-winters model, but my problem is the time series contains breaks or change point,
Should we remove the first break? Or is there any other solution ...
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1answer
216 views
How can I highlight noisy patches in a time series?
I have lots of time series data - water levels and velocities vs time. It is the output from a hydraulic model simulation. As part of the review process to confirm that the model is performing as ...
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0answers
332 views
What exactly is Beta in the Twitter Breakout Detection Algorithm?
I have been going through the R implementation of the EDM algorithm, Twitter Breakout Detection (here) and also the corresponding paper (here) and I'm not really understanding the concept of 'Beta' ...
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1answer
245 views
Judging flatness of time-series
I have multiple short (say, length <100 points) time-series as exemplified below. All the series are made of values measured in the same units. I need to find some criterion for judging their "...
