5+ Free Time Series Analysis Software


GMDH Shell is a simple yet powerful forecasting software, developed by GMDH LLC. Based on neural networks, the software allows you to easily create predictive models, as well as preprocess data with a simple point-and-click interface. GMDH Shell is much faster than other tools based on neural networks thanks to optimization of core algorithms and excellent parallel processing capabilities.

Hubstaff runs as a software on your desktop or app on your mobile device. The lightweight desktop measures activity levels as well as takes randomized screenshots, you can take up to three screenshots every ten minutes or turn the feature off altogether. The Hubstaff monitoring software allows you to view the websites and apps your team uses while tracking time. Hubstaff’s automatic payroll system simplifies paying employees and calculates pay through time tracked and the hourly rate set by the employer. Integrate Hubstaff with your favorite project management, CRM, help desk or payment tools, there are over 30 integrations available.

MacAnova is a free, open source, interactive statistical analysis program for Windows, Macintosh, and Linux. MacAnova has many capabilities but its strengths are analysis of variance and related models, matrix algebra, time series analysis (time and frequency domain), and (to a lesser extent) uni- and multi-variate exploratory statistics. Core MacAnova has a functional/command oriented interface, but an increasing number of capabilities are available through a menu/dialog/mouse type interface.

R ships with a lot of functionality useful for time series, in particular in the stats package. This is complemented by many packages on CRAN, which are briefly summarized below. There is also a considerable overlap between the tools for time series and those in the Econometrics and Finance task views. Base R contains substantial infrastructure for representing and analyzing time series data. The fundamental class is “ts” that can represent regularly spaced time series (using numeric time stamps).

Weka now has a dedicated time series analysis environment that allows forecasting models to be developed, evaluated and visualized. This environment takes the form of a plugin tab in Weka’s graphical “Explorer” user interface and can be installed via the package manager. Weka’s time series framework takes a machine learning/data mining approach to modeling time series by transforming the data into a form that standard propositional learning algorithms can process. It does this by removing the temporal ordering of individual input examples by encoding the time dependency via additional input fields.

Zaitun Time Series is a free and open source software designed for statistical analysis of time series data. It provides easy way for time series modeling and forecasting. It provides several statistics and neural networks models, and graphical tools that will make your work on time series analysis easier, and provides several statistics and neural networks models, and graphical tools that will make your work on time series analysis easier. Zaitun Time Series has a capability to deal with the stock market data. It is facilitated with the stock data type which can help the visualization of the stock market data in a candle stick graph.