JMP® Pro – The advanced analytics version of JMP®
- Advanced Modeling
- Model Comparison
- Exact Tests
Do you need JMP® Pro?
JMP Pro is the advanced analytics version of JMP that lets you use the data you have now to better anticipate the future and plan well for tomorrow. It provides all the superior visual data access and manipulation, interactivity, comprehensive analyses, and extensibility that are the hallmarks of JMP, then adds modern predictive modeling, cross-validation, exact measures of association, one-click bootstrapping and model comparison features. All of this comes in the in-memory, desktop environment familiar to current JMP users, so it can serve as the analytic hub for everyone in your organization, from beginners to power users.
Algorithms in JMP® Pro include:
- Model comparison provisions for comparing fits across multiple fit predictions.
- Model validation using train, validate and test methodology.
- Bootstrap forests, a random-forest technique.
- Gradient-boosted trees.
- Multilayer neural networks with up to three activation functions.
- Gradient-boosted neural networks with early stopping rules.
- Cross-validated stepwise regression.
- One-click bootstrapping for most statistics in JMP reports.
- Exact tests of associations with multiway contingency tables.
- Exact tests for nonparametric one-way analysis of variance.
Anyone can do a fair job of describing last year’s performance. But without the right tools and the most modern techniques, building a model to predict what will happen next year becomes much more difficult. For effective predictive modeling, you need sound ways to validate your model, and with a large model, you can easily get into trouble over-fitting.
Large models should always be cross-validated, and JMP Pro does this through data partitioning, or holdback, and visual comparison tools. Dividing the data into training, validation and test data sets has long been used to avoid over-fitting, ensuring that the models you build are not reliant on the properties of the specific sample used to build them. This produces models that generalize well to tomorrow’s data – about new customers, new processes or new risks – so you can make data-driven inferences about the future.
And while all of this is true, observational data can only take you so far. To truly understand cause and effect, many times you may wish to employ design of experiments (DOE). And JMP provides world-class tools for optimal DOE in a form you can easily use.
Time = money.
What does your analysis cost?
Get your answers fast. Weeklong projects shrink to just hours or minutes when you can build multiple models quickly and then pick the one that will generalize to future data the best. Just like that, you’re ready to move on to the next project.
JMP® Pro provides a rich set of advanced modeling techniques, including:
- Bootstrap forests (recursive partitioning).*
- Boosted trees (recursive partitioning).*
- Cross-validated logistic regression.
- Stepwise regression with stopping rules based on validation.
- Cross-validated gradient boosted neural networks with two levels and three activation functions.*
- Principal component variable clustering prior to modeling.
- Cross-validated partial least squares regression with missing value imputation.
* Generates SAS code ready for use with SAS Model Manager
As one of the SAS offerings for predictive analytics and data mining, JMP Pro can easily connect to SAS, expanding your options and giving access to the unparalleled depth of SAS Analytics and data integration. With or without an active SAS connection, JMP Pro can output SAS code to score new data quickly and easily with models built in JMP.
Performance – find the most useful model easily and visually
“All models are wrong, but some are useful.”
– George E. P. Box
In the real world, some kinds of models fit well in certain situations but fit poorly in others. With JMP Pro, there are many ways to fit, and you need to find out which one is most appropriate in a given situation.
Using model comparison in JMP Pro, you can compare all the saved prediction columns from various fits and pick the best combination of goodness of fit, parsimony and cross-validation. JMP Pro makes this comparison automatically and then compares the models in many ways, using traditional or alternative measures of fit. At the same time, you can interact with visual model profilers to see which important factors each model is picking up.
Measures of fit, diagnostic plots and profilers are reported for easy comparison of models to help you determine the right path forward.
Exact tests enable you to make reliable inferences when your data is small, sparse, heavily tied or unbalanced, and the assumptions and approximations of the corresponding large sample theory are in doubt.
For contingency analysis, JMP Pro provides exact versions of Fisher’s test (for association between rows and columns), the Cochran-Armitage test (for trends in binomial proportions across the levels of a second variable) and the Kappa statistic (for testing agreement between two variables that have the same levels).
In the Oneway platform, JMP Pro provides exact versions of the Wilcoxon (Mann-Whitney), Median, Van der Waerden and Kolmogorov-Smirnov tests whenever the X variable has two levels.
All exact tests are integrated in the Fit Y by X platform, and they become available only when the selected X’s and Y’s satisfy the correct conditions. This allows users of all skill levels to utilize inferential methods that will remain reliable in any real-world situation.
Assign measures of precision to model predictions
Bootstrapping approximates the sampling distribution of a statistic. JMP Pro is the only statistical software package that lets you bootstrap a statistic without writing a single line of code. One-click bootstrapping means you are only a click away from being able to bootstrap any quantity in a JMP report.
This technique is useful when textbook assumptions are in question or don’t exist at all. For example, try applying bootstrapping techniques to nonlinear model results that are being used to make predictions or determining coverage intervals around quantiles. Also, you can use bootstrapping as an alternative way to gauge the uncertainty in predictive models. Bootstrapping lets you assess the confidence in your estimates with fewer assumptions – and JMP Pro’s one-click bootstrap makes it easy.
Share your discoveries
JMP has always been about discovery and finding the best way of communicating those discoveries across your organization.
JMP Pro includes all the visual and interactive features of JMP, making your data accessible in ways you might have never experienced. Through dynamically linked data, graphics and statistics, JMP Pro brings your investigation alive in a 3-D plot or an animated graph showing change over time, generating valuable new insights that inform both the model-building and explanation process.
JMP Pro helps you construct a narrative, and interactively communicate findings in ways others can readily understand and act upon.