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• MARS是一个先进的计量预测软件,它包括数据库、自建模系统、优化系统,适用于材料研究数据和生产数据的管理,多元非线性建模,以及多因子、多目标优化。
  
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• 自动非线性回归
  MARS建模引擎非常适合那些喜欢与传统回归相似的结果，同时捕获基本非线性和相互作用的用户。MARS方法的回归建模方法有效地揭示了重要的数据模式和关系，这些模式和关系即使不是不可能，也很难被其他回归方法揭示出来。MARS建模引擎通过将一系列直线拼接在一起来构建其模型，每条直线允许自己的斜率。这允许MARS建模引擎跟踪数据中检测到的任何模式。
• 高质量的回归和分类
  MARS模型旨在预测数字结果，例如移动电话客户的平均每月账单或购物者预期在网站访问中花费的金额。MARS引擎还能够为是/否结果生成高质量的分类模型。MARS引擎自动且高速地执行变量选择，变量变换，交互检测和自检。
• 高绩效结果
  MARS发动机表现出非常高性能的领域包括预测发电公司的电力需求，将客户满意度评分与产品的工程规范相关联，以及地理信息系统（GIS）中的存在/不存在建模。
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• MARS software is ideal for users who prefer results in a form similar to traditional regression while capturing essential nonlinearities and interactions. The MARS approach to regression modeling effectively uncovers important data patterns and relationships that are difficult, if not impossible, for other regression methods to reveal. MARS builds its model by piecing together a series of straight lines with each allowed its own slope. This permits MARS to trace out any pattern detected in the data.
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• HIGH-QUALITY PROBABILITY
  The MARS model is designed to predict continuous numeric outcomes such as the average monthly bill of a mobile phone customer or the amount that a shopper is expected to spend in a web site visit. MARS is also capable of producing high quality probability models for a yes/no outcome. MARS performs variable selection, variable transformation, interaction detection, and self-testing, all automatically and at high speed.
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• HIGH-PERFORMANCE RESULTS
  Areas where MARS has exhibited very high-performance results include forecasting electricity demand for power generating companies, relating customer satisfaction scores to the engineering specifications of products, and presence/absence modeling in geographical information systems (GIS).