4
votes
1answer
195 views

Detecting Outliers in Time Series (LS/AO/TC) using tsoutliers package in R. How to represent outliers in equation format?

Comments: Firstly I would like to say a big thank you to the author of the new tsoutliers package which implements Chen and Liu's time series outlier detection which was published in the Journal of ...
0
votes
0answers
10 views

Significant difference real or due to the internal variability?

In my data I have 9 different sets of data for 2 different groups. Each one of these datasets is the same measurement changing over the time. If I make a graph, I can see 9 lines for each group. I did ...
3
votes
2answers
202 views

Detecting outliers using correlogram

If there is an outlier in a time series, how does its correlogram behave? Is it possible to find outliers using a correlogram? EDIT I have such a Time series: ...
0
votes
0answers
33 views

Detecting outliers using periodogram?

I would like to find outliers in a time series. If there is a an outlier in a time series, how does its periodogram behave? For example I have a time series with 10 elements, and I think 515 in this ...
2
votes
1answer
76 views

Detecting outlier cash movements

If I'm watching a series of accounts for transactions going in and transactions going out, I want to notice unusually large or transactions for any particular account on any particular day. So if ...
1
vote
0answers
396 views

Outlier detection and smoothing for multi dimensional time series

From kinect depth images, I have collected the following time series that represent the features = 3D joint positions, quarternion angles, difference between hip joint and centroid of the right arm ...
1
vote
1answer
212 views

Finding anomalies using moving average in a time series [duplicate]

I want to find anomalies in a time series. Is it possible to find anomalies using moving average?
1
vote
1answer
155 views

Moving average filter for outlier removal

I am using a moving average filter to smooth data for outlier removal. By changing the number of average points, I am getting different result. My data are multi-dimensional feature vectors. I ...
1
vote
1answer
162 views

Outlier treatment in Vector Autoregression (VAR) Model

Data: Multivariate Time Series, Series 1) Demand of a product 2) Rainfall data both available at monthly level from 2010-2013. Approach: I am trying to estimate the effect of rainfall on demand of ...
1
vote
3answers
334 views

How to correct outliers once detected for time series data forecasting?

I'm trying to find a way of correcting outliers once I find/detect them in time series data. Some methods, like nnetar in R, give some errors for time series with big/large outliers. I already managed ...
0
votes
1answer
123 views

Detecting outliers in a time-series

I'm trying to exclude the outliers using 2-sigma rule and I have a time series. So I use a moving average for this. Let's say I have this: ...
0
votes
1answer
71 views

Weighting time series coefficients using model's likelihood

I have a question regarding to time series forecasting. In particular I've been working with a Bayesian approach, but I think the question is independent from that. I have several time series which ...
2
votes
0answers
384 views

Outlier detection in time series data

I checked different questions on similar topics, but none were exactly the answer I wanted and I am confused. I am working with big data, the data has a bursty nature with high frequency. I ...
1
vote
2answers
96 views

Removing outliers and calculating a “lowest” attainable price from a pre-determined/fixed time series of prices

Just a foreword, I'm not a mathematician or otherwise statistically skilled. I know my way around calculating standard deviations, but it's all self taught. I'm a programmer with limited stats ...
1
vote
0answers
207 views

Outlier detection of an unevenly spaced time series

I found the Rob H answer to this question very interesting and works pretty well. However, I also would like to apply this methodology to an unevenly spaced time series like the following: ...
2
votes
2answers
195 views

How to identify spikes in a noisy time series?

I have time-series data of brain cell spiking. It's basically got a baseline of random noise with large spikes interspersed. I want to be able to algorithmically cluster the spike portions of the ...
10
votes
1answer
611 views

How do I incorporate an innovative outlier at observation 48 in my ARIMA model?

I am working on a data set. After using some model identification techniques, I came out with an ARIMA(0,2,1) model. I used the detectIO function in the package ...
6
votes
0answers
188 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
97 views

Filtering outliers from geo-spatial-temporal log

I have downloaded my Latitude location history from Google for the time of about three years and now I'd like to, for starters, visualize where I've been. It turns out that the history contains some ...
1
vote
0answers
55 views

Spotting anomalies in time series [duplicate]

Possible Duplicate: Simple algorithm for online outlier detection of a generic time series I've got data on quantities sold and average price, by date, for a number of commodities and a ...
3
votes
0answers
59 views

Detecting outstanding events [duplicate]

Possible Duplicate: Simple algorithm for online outlier detection of a generic time series Observing the time series data I noticed there are some outstanding peaks (the picture below). I ...
6
votes
1answer
581 views

STL on time series with missing values for anomaly detection

I am trying to detect anomalous values in a time series of climatic data with some missing observations. Searching the web I found many available approaches. Of those, stl decomposition seems ...
1
vote
2answers
317 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 ...
5
votes
4answers
2k views

How to fit a model for a time series that contains outliers

I have fitted ARIMA(5,1,2) model using auto.arima() function in R and by looking order we can say this is not a best model to forecast. If outliers exist in the ...
2
votes
1answer
271 views

Treatment of outliers in annual time series data

I have an annual time series of data of a growth-rate variable $X$ for 50 years. Most of the values for the variable $X$ are less than 10%. The exception are two values that are around 30%. How do I ...
3
votes
3answers
595 views

Univariate clustering of time series

I just want to know if its possible to cluster an univariate time series, in order , say, to detect anomalies? and do you have any online version for denstream code, in Matlab? here is the time ...
2
votes
1answer
809 views

C++ library to play with statistics (detecting outliers in time series)

I am looking for a C++ library for statistics to play with outliers detection in time series (amongst other). What I need: Robust estimators, correlations, hypothesis tests, etc; No dependencies ...
4
votes
2answers
295 views

How to judge if a datapoint deviates substantially from the norm

This is Statistics 101, but I'm not a statistician and so can't seem to find the right technical jargon to google. My company collects data at discrete points through time. Today's datapoint is ...
1
vote
0answers
49 views

Modeling a TAR model that can handle the problem of outliers in nonlinear data

Can somebody please share idea on how I can model a TAR model that can handle outliers in nonlinear data? I need to compare such model with the general form of TAR model. Which computer software can ...
3
votes
5answers
1k views

Use of robust spread measures such median average deviation and median filters for time series

I have a time series where I need to detect gross anomalies due to coding errors, not small shifts in the structure of the series. I am interested in the most recent data points, not historical data ...
5
votes
3answers
2k views

Outliers spotting in time series analysis, should I pre-process data or not?

My question builds on a previous post on outlier detection in generic time series, and specifically on the answer provided by the always great Rob H. I work for a small-sized manufacturing company ...
2
votes
1answer
131 views

Find outlier in time domain dataset

We're analyzing a bunch of time domain signals, I want to be able to identify an outlying one. In our results all the signals will either all be reasonably similar, or in some cases, one should be ...
1
vote
1answer
479 views

Bonferroni for outlier detection?

I am reading a book on time series analysis and I am having problems understanding the section about outlier detection. The authors say that when you want to know whether at a certain time $T$ there ...
2
votes
1answer
246 views

Outlier detection in short time series with two seasonalities

I have short daily time series (less than 4 years) representing sales and exhibiting two seasonalities (weekly and yearly) and I am seeking to identify outliers (not only data reporting errors but ...
4
votes
2answers
822 views

Outlier detection for generic time series

In this case, "generic" being the entire gauntlet of macroeconomic time-series that private and government statistical offices put out. Some background - I recently started working at a data provider ...
6
votes
5answers
1k views

Automatic threshold determination for anomaly detection

I am working with a time series of anomaly scores (the background is anomaly detection in computer networks). Every minute, I get an anomaly score $x_t \in [0, 5]$ which tells me how "unexpected" or ...
16
votes
5answers
749 views

Can data cleaning worsen the results of statistical analysis?

An increase in the number of cases and deaths occurs during epidemics (sudden increase in numbers) due to a virus circulation (like West Nile Virus in USA in 2002) or decreasing resistance of people ...
11
votes
3answers
4k views

Robust outlier detection in financial timeseries

I'm looking for some robust techniques to remove outliers and errors (whatever the cause) from financial time-series data (i.e. tickdata). Tick-by-tick financial time-series data is very messy. It ...
34
votes
11answers
11k views

Simple algorithm for online outlier detection of a generic time series

I am working with a large amount of time series. These time series are basically network measurements coming every 10 minutes, and some of them are periodic (i.e. the bandwidth), while some other ...
15
votes
3answers
2k views

Application of wavelets to time-series-based anomaly detection algorithms

I've been beginning to work my way through Statistical Data Mining Tutorials by Andrew Moore (highly recommended for anyone else first venturing into this field). I started by reading this extremely ...