Multi-Model Time Series Analysis

The folks at ELEKS discuss what to do when a single time series model just won’t cut it:

With the emergence of the powerful forecasting methods based on Machine Learning, future predictions have become more accurate. In general, forecasting techniques can be grouped into two categories: qualitative and quantitative. Qualitative forecasts are applied when there is no data available and prediction is based only on expert judgement. Quantitative forecasts are based on time series modeling. This kind of models uses historical data and is especially efficient in forecasting some events that occur over periods of time: for example prices, sales figures, volume of production etc.

The existing models for time series prediction include the ARIMA models that are mainly used to model time series data without directly handling seasonality; VAR modelsHolt-Winters seasonal methods, TAR modelsand other. Unfortunately, these algorithms may fail to deliver the required level of the prediction accuracy, as they can involve raw data that might be incomplete, inconsistent or contain some errors. As quality decisions are based only on quality data, it is crucial to perform preprocessing to prepare entry information for further processing.

Treating time series data as a set of waveform functions can generate some very interesting results.

Related Posts

Road Construction Incentive Contracts And R

Sebastian Kranz promotes an interesting RTutor project: Patrick Bajari and Gregory Lewis have collected a detailed sample of 466 road construction projects in Minnesota to study this question in their very interesting article Moral Hazard, Incentive Contracts and Risk: Evidence from Procurement in the Review of Economic Studies, 2014.They estimate a structural econometric model and find that […]

Read More

Analyzing Customer Churn With Keras And H2O

Shirin Glander has released code pertaining to a forthcoming book chapter: This is code that accompanies a book chapter on customer churn that I have written for the German dpunkt Verlag. The book is in German and will probably appear in February: https://www.dpunkt.de/buecher/13208/9783864906107-data-science.html.The code you find below can be used to recreate all figures and analyses from this […]

Read More

Categories

November 2016
MTWTFSS
« Oct Dec »
 123456
78910111213
14151617181920
21222324252627
282930