Linked Questions
30 questions linked to/from Simple algorithm for online outlier detection of a generic time series
2
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answer
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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?
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3
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0
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237
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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 would ...
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1
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0
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194
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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 number ...
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0
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0
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156
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Getting rid of sparks in sample data [duplicate]
Possible Duplicate:
Simple algorithm for online outlier detection of a generic time series
Getting rid of spikes in sample data
How could I get rid of sparky (aka spikey) data in a discrete ...
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3
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0
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Application to a real life problem: identifying outliers in univariate time series data [duplicate]
I have a rather simple problem that I'm having trouble deciding an answer upon. As a student studying Statistics I'm very familiar with terminology and theory but I suppose I'm stumped on my first ...
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2
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Anomaly detection within periodic time series [duplicate]
I would like to detect anomalies in a time series data using a moving average approach. Basically, the system will rise an alarm when a data point is far away (3*std for example) from the current mean....
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0
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Getting rid of spikes in sample data [duplicate]
Possible Duplicate:
Simple algorithm for online outlier detection of a generic time series
How could I get rid of sparky data in a descrete data set, but in a "smoother out" manner?
Take for ...
- 101
61
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7
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38k
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Period detection of a generic time series
This post is the continuation of another post related to a generic method for outlier detection in time series.
Basically, at this point I'm interested in a robust way to discover the periodicity/...
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18
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3
answers
10k
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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 ...
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15
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5
answers
40k
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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 ...
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8
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3
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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 ...
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8
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3
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2k
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How to fit a robust step function to a time series?
I have a somewhat noisy time series that hovers around different levels.
For example, the following data:
I have the solid line data available, and I would like to obtain an estimate for the dashed ...
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12
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4
answers
2k
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Outlier Detection in Time-Series: How to reduce false positives?
I'm trying to automate outlier detection in time-series and I used a modification of the solution proposed by Rob Hyndman here.
Say, I measure daily visits to a website from various countries. For ...
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1
vote
3
answers
6k
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Trend Analysis: How to tell random fluctuations from actual changes in trends?
I hope somebody in here can help me: I'm looking for some pointers as to how to distinguish random fluctuation from actual changes in trends, e.g.:
In a time series with measures taken at monthly (...
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4
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2
answers
2k
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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 ...
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3
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1
answer
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Median absolute deviation only can be used for anomaly detection for time series without a trend?
I think MAD only can be used to detect anomalies for time series without a trend because it relies only a stable median to detect anomalies. It should be OK for time series with seasonality. Just seek ...
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4
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4
answers
2k
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High-Frequency Time-Series Forecast With A Lower Bound
I am helping a friend with a data project. He's interested in building a canary-in-the-coal-mine alert system for his website which tells him when the number of users dips below some critical lower ...
- 33.5k
10
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2
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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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2
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1
answer
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Outlier detection in ARIMA model with R
After fitting my time series with an ARIMA model, I want to test outliers in the residuals' series. Are there any functions in R that could do this test and furtherly test whether the outlier is ...
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3
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1
answer
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Simple algorithm for online outlier detection of a generic time series II: Daily cycle within annual
I have several years of sensor data (temperature and relative humidity) that records every 1/2 hour. When the sensor dies, it often starts throwing bad data mixed in with good data before it dies ...
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1
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1
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How can I calculate the stability of my dataset?
Forgive my ignorance, I am not a mathematician or statistician. I'll try to explain as clearly as I can.
I have a dataset (image below). The data represents delays of some signal over time. The large ...
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0
answers
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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 ...
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3
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0
answers
873
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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:
...
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1
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1
answer
409
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Boxplot Outliers
I'm looking for outliers in a non-normally distributed dataset:
n: 1,900
Mean: 2,738
StDev: 1,544
Min: 1
Max: 22,102
Anderson-darling: 40
P < 0.005
The boxplot shows the outliers in one ...
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4
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1
answer
265
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Testing for a drop in bookings
We're developing real-time alerts for fine-grained (every 5 minutes) time series bookings data, and I'm looking for the best approach to doing this. Idea is that if over the past 10–15 minutes (say) ...
user11284
1
vote
0
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418
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Detect periodes of irregular patterns in time series data
This plot shows hourly time series data of a households power usage. The house is only occupied for short periods.
What simple alg. or technique can I use to find the start of these irregularities?
...
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2
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0
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344
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How to detect a relatively small level shift(leakage) in an hourly water flux time series in an area?
Background
I'm working on a project which aims to use the history data about a water flux to detect whether there is a leakage happened. The data is hourly collected and among about 4 months.
I've ...
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1
vote
1
answer
155
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Removing outliers at the start when there are multiple ANOVA and correlational analyses in a single results section [duplicate]
I would be grateful for opinion on which of the two options below (or an alternative) is best:
Summary of study: In a single results section, different ANOVAs are run on the different metrics – raw ...
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0
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0
answers
124
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Real-time anomaly detection for online time -series
I am new to the anomaly detection world and am dealing with a project to detect real-time anomalies for a time-series in a fraud detection schema. I read the answer by Rob Hyndman here and like the ...
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1
vote
1
answer
103
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Fix wrong data coming from a sensor
I have data coming from a sensor that I store in a time serie.
When I graph them, I obtain:
These data are supposed to be "continuous", like temperatures, not going up and down so fast.
After ...
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