JMP® for Analytical Application Development
JMP software has always supported statistical discovery through its unique combination of interactive graphics and wealth of built-in statistics. In addition to its out-of-the-box functionality, JMP serves as an analytic hub, allowing you to quickly and easily build and share custom applications that leverage just the right JMP feature along with your other favorite analytical software.
You can call both SAS and R to expand your data management and analytic repertoire as needed, surfacing only the required capability within JMP’s familiar point-and-click world. Once you have created your application, you can take advantage of the new add-in architecture in JMP to package and deploy it efficiently.
Think of JMP as your personalized statistical workbench for constructing tailored applications in any problem context you choose.
- SAS
- R
- Personalization
SAS is world-renowned for its data access and data management, as well as the depth and breadth of its tried and tested analytics. JMP is a client to SAS, but designed for exploratory data visualization. JMP can work with other SAS technologies in many ways. This opportunity for integration opens up powerful SAS capabilities to new pockets of users who are already comfortable working with JMP’s intuitive dashboard. Whether you want to broaden your SAS usage to maximize your current investment – or increase the capacity of JMP’s interactive data visualization – consider building an analytical application that utilizes the extensive SAS Analytics you need in the familiar JMP environment you enjoy.
This SAS add-in for LOESS regression combines the power of SAS and the convenience of JMP.
JMP integrates with the R open-source statistical programming language. This means R programmers can quickly leverage the interactive graphics in JMP to provide the much-needed multiple dynamic views that are so useful for data exploration and model interpretation. Conversely, JMP users can exploit any of the cutting-edge statistical functionality the open-source community provides – without being exposed to unnecessary and distracting complexity. You can exchange data between JMP and R, submit R code from JMP within a JMP script, and render R graphics directly in JMP. Combining these elements allows R developers who know a little JMP, or JMP developers who know a little R, to build JMP add-ins that use the advanced capabilities in R whenever they are valuable, surfacing them in a way that is appropriate for any user.
Employ a JMP add-in that calls R to perform classification using a support vector machine.
Make JMP your own…or somebody else’s. You don’t have to be a programmer to use JMP. But if you are – or if you just like to tinker – you can use the rich JMP Scripting Language (JSL) to customize, re-package, or extend JMP functionality for yourself and others. JMP allows you to automate your favorite analyses and customize reports via JSL. Its flexibility permits you to create sophisticated user interfaces, work with other analytical software, and build JMP add-ins – customized statistical discovery applications to share with other JMP users. This enables you to easily spread the use of analytics throughout your organization, wherever data is available and data-driven decisions are needed. Find an add-in or contribute one of your own in the JMP File Exchange.
Utilize a JMP add-in that performs Savitzky-Golayfiltering of spectral data entirely in JMP.
More resources for Analytical Application Development
Demos
Aerospace Systems Design Lab Success Story Demo
On-Demand Webcasts
On the JMP Blog
Other Resources
The Power of Personalization with JMP (2010 SGF Paper, Ian Cox)
Book: JUMP Into JMP Scripting (Wendy Murphrey& Rosemary Lucas)
Contact JMP Sales
+44 (0) 1628 490 200
+44 (0) 01628 486 933
