Strengths and Limitations

A word of caution regarding the quality of R algorithms: R comes without warranty or guarantees. In practice, many of the algorithms available in R are the result of diligent work over many years by one or a few individuals who are experts in the respective methodology or domain. However, this does not mean that the software was created following rigorous software development lifecycle methodology, or stringent standard operating procedures for software requirements gathering, design, implementation, and testing. Therefore, in order to build a mission-critical or validated application around a component that depends on R, it is absolutely critical that you carefully validate all results for the use cases to which the software is to be applied.

A word of caution regarding scalability, large data sets, etc: Another caveat regarding R that needs to be considered before building solutions around R concerns its basic architecture. Unlike Statistica, data in R must be (in practically all cases) resident in the computer’s memory. This restriction, in combination with hardware-level and operating system-level memory limitations, may or may not pose an obstacle for any one individual user, but will need to be considered carefully when building R-based server applications accessible to multiple users.