SAS Institute Inc. (“SAS”) is an American multinational developer of analytics software based in Cary, North Carolina. The company has around 14,000 employees.
SAS started as a project at North Carolina State University to create a statistical analysis system used mainly by agricultural departments at universities in the late 1960s.
SAS is the name of their software suite that can mine, alter, manage and retrieve data from a variety of sources and perform statistical analysis on it. It has more than 200 components covering areas including statistical analysis, econometrics and time series analysis, an interactive matrix language, data mining and much more.
SAS/ETS software, a component of the SAS System, provides SAS procedures for econometric analysis, time series analysis, time series forecasting, systems modeling and simulation, time series data management, and more.
SAS is proprietary software. What are the best free and open source alternatives to SAS/ETS?
R is a statistical programming language that can be used for data manipulation, visualisation of data and statistical analysis. The R language consists of a set of tokens and keywords and a grammar that you can use to explore and understand data from many different sources.
R offers a huge range of functions for every data manipulation, statistical model, or chart which is needed by the data analyst. R offers inbuilt mechanisms for organizing data, running calculations on the given information and creating graphical representations of that data sets.
Learn R with our recommended free books and free tutorials.
gretl is a cross-platform software package for econometric analysis, written in the C programming language. It offers an intuitive graphical user interface, a wide variety of estimators: least squares, maximum likelihood, GMM; single-equation and system methods; regularized least squares (LASSO, Ridge, elastic net), a good range of time series methods, limited dependent variables, and panel-data estimators, including instrumental variables, probit and GMM-based dynamic panel models.
There’s also an integrated powerful scripting language (known as hansl), with a wide range of programming tools and matrix operation.
Grocer is an open source econometric toolbox particularly devoted to time series for Scilab, a matrix-oriented software.
This software performs most usual econometric tasks that commercial software perform (single and multiple regression methods, diagnostic testing, VAR methods, unit roots and cointegration methods, Kalman filtering, etc). It contains a time series object, which allows all usual operations.
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|Alternatives to SAS's Products|
|Base SAS is a fourth-generation programming language (4GL) for data access, data transformation, analysis and reporting. It is included with the SAS Platform.|
|JMP (pronounced “jump”) is a suite of computer programs for statistical analysis. JMP software combines interactive visualization with powerful statistics.|
|SAS Enterprise BI Server provides a solid basis for vendor consolidation and BI standardization, enabling IT to focus on more effectively aligning with the business.|
|SAS Enterprise Miner aims to streamline the data mining process. It helps you analyze complex data, discover patterns and build models so you can more easily detect fraud, anticipate resource demands and minimize customer attrition.|
|SAS/ETS provides SAS procedures for econometric analysis, time series analysis, time series forecasting, systems modeling and simulation, time series data management, and more.|
|SAS/GRAPH is a data visualization tool that lets you create effective, attention-grabbing graphs. It consists of a collection of procedures that let you provide a variety of charts, plots, 3-D scatter/surface plots, and more.|
|SAS/IML is a powerful, flexible matrix programming language for interactive and exploratory data analysis.|
|SAS/INSIGHT is a tool for data exploration and analysis. Explore data through graphs and analyses linked across multiple windows.|
|SAS/STAT provides tools and procedures for statistical modeling of data. It includes analysis of variance, linear regression, predictive modeling, statistical visualization techniques and a lot more.