2
votes
1answer
42 views

Understanding factor potentials in PyMC

I'm trying to understand factor potentials from the PyMC documentation, but need some help on the implementation piece--or it may turn out that I am misunderstanding how potentials work altogether. ...
3
votes
1answer
51 views

Checking that values are piecewise uniform

I have a set of values and I wish to check if they are piecewise uniform. I hope I'm using the correct terms, but I'll explain what I mean. Consider the following values - 100,105,100,103,98. We ...
1
vote
1answer
50 views

The concept of “average run length” in change point detection

With respect to the change point detection for data stream, there is a concept of "average run length", which is discussed in the CPM package manual: I am not clear why that "average number of ...
1
vote
1answer
76 views

How to analyze data which might come from a few normal distribution concatenate together in order?

For example, I have a series of values for example like the following: data <- c(rnorm(10000,40,1500),rnorm(9000,-35,1400),rnorm(11000,30,1300)) I don't know ...
1
vote
0answers
79 views

How to detect step changes in GPS time-series data?

The graph below shows GPS heading data (sampled every second) and I am trying to find the best way to detect (right/left) turns in the data. Appreciate suggestions for algorithms/methods for it ...
0
votes
0answers
41 views

Detection of activity areas in time series

I am working on 4-dimension time series in which I would like to detect anomaly patterns with varying lengths and shapes. The time-series are residuals generated by an evolving clustering method. The ...
4
votes
1answer
331 views

Python module for change point analysis

I'm looking for a Python module that performs a change-point analysis on a time-series. There are a number of different algorithms and I'd like to explore the efficacy of some of them without having ...
6
votes
0answers
127 views

Link Anomaly Detection in Temporal Network

I came across this paper that uses link anomaly detection to predict trending topics, and I found it incredibly intriguing: The paper is "Discovering Emerging Topics in Social Streams via Link Anomaly ...
2
votes
1answer
280 views

Testing whether there is an increase between two regression slopes in a time series

I have a data of sea levels from a particular station from 1940 till today. The linear regression on the data from 1940-1980 resulted in a slope of 3. The linear regression on the data from 1980-2010 ...
4
votes
1answer
151 views

How to test for a break in a time series cycle

I've been scratching my head over this issue and would appreciate some help. I have a time series from 1920-2011 which I've used a Baxter Kings filter on to detrend. I would like to test whether the ...
2
votes
1answer
505 views

Tools to detect jumps in a linear time series

I have a financial time series that has a linear down trend, but sometimes a jump happens (see image below). What statistical methods can I use to detect these jumps as early as possible?
2
votes
1answer
156 views

How can I measure the effects certain events have on the frequency of other events over time?

EDIT: added more details following @kjetil comments I have the following problem: I monitor one stream of events of type A - those events can be considered instantaneous. I also monitor additional ...
1
vote
1answer
90 views

Model to detect abnormalities in two-value data?

I have a question concerning data that oscillates between two primary value ranges, and how one might go about determining any performance metrics or abnormalities in that data. Example: I have a ...
3
votes
0answers
110 views

Reference for implementing generalized likelihood ratio test to determine online whether time-series mean has shifted

What is a reference that describes the "generalized likelihood ratio" test to determine online (i.e., meaning that we add an observation, then check, then add an observation, then check) whether the ...
4
votes
1answer
739 views

How to interpret coefficients in a regression with ARIMA errors?

I've got some time-series business data that I can fit relatively well with a ARIMA(2,1,0)(1,1,0)[12] model (using R's excellent ...
3
votes
3answers
462 views

Identify different periods of variance in a time series

I have a time series $x_t$ which may go through different phases of volatility. One example might be some stock that has high variance from 9 AM to 11 AM, low variance from 11 AM to 2 PM, and then ...
1
vote
2answers
288 views

Filtering techniques and noise

Suppose we have some house price data for 30 years (1970-1999). This is yearly data (30 data points). Suppose some major event $X$ happened on 1980. I want to see whether this event affected prices ...
4
votes
2answers
388 views

How to detect changes in amplitude?

I have timeseries like this: as you can see there are changes regarding the amplitude. Is there a test to check this kind of changes? Important annotations: I do not know if the series have ...
6
votes
2answers
921 views

Detecting steps in time series

I've attached a picture of the time series I'm talking about. The top is the original series, the bottom is the differenced series. Each data point is a 5 minute average reading from a strain gauge. ...
3
votes
1answer
312 views

Is is possible (or advisable) to do Change Point Analysis on sequence of groups with R?

I'm familiar with post-hoc testing with ANOVA for exploring differences between a sequence of groups, but recently I've been reading about Change Point Analysis ...
8
votes
2answers
125 views

State of the art method(s) to find zero mean portions of a time series

I have noisy time series which I need to segment into those portions with a zero mean and those portions without a zero mean. Finding the boundaries as accurately as possible is important (clearly ...
11
votes
6answers
2k views

How to detect a significant change in time series data due to a “policy” change?

I hope this is the right place to post this, I considered posting it on skeptics, but I figure they'd just say the study was statistically wrong. I'm curious about the flip side of the question which ...
1
vote
5answers
2k views

How to detect structural change in a timeseries

Is there a specific method to detect change points(structural breaks) in a timeseries?(stocks prices) Thanks
0
votes
0answers
305 views

How to use gradient to obtain critical points of Time series?

How to determine the number of critical points for some time series (for example, using gradient)? As far as I understand I have to do the following steps: Fit the time series with some "curve" ...
1
vote
1answer
180 views

Number of segments to divide a time-series

Suppose we have time-series $ X_t $ and it has the following decomposition $$X_t=\mu + \varepsilon_t,$$ where $\mu$ is a mean and $\varepsilon_t$ - the error term. The model complexity will ...
6
votes
2answers
551 views

Automatically detecting sudden change of mean

Take a look at this photo: It depicts a box plot of series of identical runs for successive i values. (AFAIK it's the standard Min/Max and 1rst, 2nd, 3rd quartiles.) So the x-axis of 1 represents ...
11
votes
1answer
697 views

Determining if change in a time series is statistically significant

I have the total number of calls received each week and have plotted them on a chart, going back nearly 3 years. By eye it seems that there was a massive drop over Christmas, that doesn't seem to ...
6
votes
1answer
847 views

Chow test or not?

I am trying to set up an automatic screen to detect structural breaks in large numbers of time series. The time series are weekly and represent behaviour of customers. I have set up a Chow test. I ...
8
votes
2answers
2k views

Detect changes in time series

I came across a picture of an application prototype that finds significant changes ("trends" - not spikes/outliers) in traffic data: I want to write a program (Java, optionally R) that is able to ...
2
votes
1answer
443 views

Time-series data pre-aggregated into non-stationary rolling 12-month periods: are there special considerations for modeling?

I'm exploring the use of changepoint detection or other methods (am slowly becoming aware of wavelet transformation, etc. but have tons to learn in this area) to identify key shifts in health care ...