30 questions linked to/from Simple algorithm for online outlier detection of a generic time series
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/...
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 ...
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 ...
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 ...
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 ...
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 ...
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 ...
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 ...
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) ...
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 ...
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 ...
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 ...
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: ...
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 ...
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 ...