Internal Use Only
- Projects
Many JMP users have requested a tool to help them with workspace layout and session management. When many data tables, scripts and reports are open at once, it can be challenging to find a desired report. It can also be challenging to separate groups of data tables and reports into individual analysis projects, and running JMP with windows maximized can make it hard to use the multiple windows that may be open. The project system aims to solve many of these common problems.
Projects provide a single document interface to JMP with a tabbed workspace that is easy to customize, a place to bookmark files and a window list that lets the user see and easily move to any open window, data table or script. The project also lets the user bookmark and launch supporting files like .pdf, .word and .ppt documents. Projects can also be used to quickly open and close many files belonging to one or more analyses and to save the state of an analysis session; it can also be used to keep two or more projects separate rather than running multiple JMP sessions, as was required in the past.
Finally, for those users who need to run repeated data queries, analyses and reports, the project feature affords a quick way of collecting a set of workflow tasks and gives them an easy way to share, save and collaborate.
Highlights
- Single document interface to JMP.
- Pick and choose files to include.
- Organize a reconfigurable workspace.
- Share and archive analyses.
- Launch supporting documents (.ppt, .word, .pdf) directly from JMP.
- Graph Builder Improvements
Graph Builder is the toolbox that helps users find and tell the stories within their data. In JMP 14, Graph Builder adds Packed Bars, a new bar type combining ideas from treemaps and Pareto plots, and adds several features designed to give users finer control over graph customizations. Bootstrapped confidence intervals can now be added to smoothers, error bars are completely customizable, and a wider variety of descriptive statistics can be displayed directly on graphs. All of these features combine to further the publication-readiness of Graph Builder’s results.
Highlights
- New bar type: Packed Bars.
- More control over graph customization.
- Easily incorporated customized error bars.
- Marker Sizes from legend.
- Point dodging and jittering options.
- More control over contours including smoothing and shape clipping.
- Bootstrap confidence intervals for Smoother element.
- Support for more basic statistical analysis directly in Graph Builder.
- Recode Refresh
Ensuring the consistency and accuracy of categorical data has always been one of the most time-consuming and tedious aspects of data cleanup, but Recode in JMP 14 aims to change that. With regex support, improved filtering and text parsing options, support for multiple response data and value labels, and integration with the Formula Depot in JMP Pro, you won’t trust your data cleansing to any other tool.
Highlights
- Search box allows more control over filtering.
- Improved Text Parsing.
- RegEx support.
- Import recode results column.
- Create, consume and convert value labels directly from Recode.
- Publish recode formula to Formula Depot, which lets you perform data cleanup inline in a production environment without having to bring the data into JMP.
- Support for multiple response columns.
- Group to new category.
- Recode numeric continuous columns.
- Multiple File Import
Efficiently and accurately combining hundreds or thousands of files into a single one used to require writing a JSL script, but no longer. In JMP 14, you can import multiple files into a single data table, or a collection of data tables, with just a few clicks. Specify import options, filter files by a variety of criteria, and import to a single column (for use with Text Explorer) or into a multi-column table.
Highlights
- Load several files into a data table.
- Filter files by size, date, name and type.
- Support for one-column import, useful for Text Explorer document preparation.
- Within platform support for editing text import options.
- Text Explorer Updates
Text Explorer was an exciting addition to JMP 13, letting users explore unstructured text data in a point-and-click environment. Now Text Explorer is even more useful, adding more powerful report filters, Chinese and Japanese language support, per-topic word clouds, and in JMP Pro, discriminant analysis and validation column support.
Highlights
- Support for Asian languages in Text Explorer (Chinese and Japanese).
- Better filtering options for tabular output in Text Explorer, including terms, phrases and report lists.
- Per topic word clouds.
- Support for discriminant analysis (JMP Pro).
- Support for validation column in the platform launch for use in a predictive modeling workflow (JMP Pro).
- New Data Table Features
All JMP users use data tables, and in JMP 14, we’ve made data tables even more powerful and easier to use. Now tables can use the values of any column – even an image column – as markers; store hyperlinks to webpages, files and JSL scripts; and perform several new single-click transforms. JMP 14 also has more powerful Virtual Joins and a new utility to easily convert between value labels and codes.
Highlights
- Use for marker column option.
- Paste into cell.
- Grouping and nesting of table scripts for better script organization.
- Clickable Links afforded by the Event Handler column property.
- Labels to codes and Codes to labels columns utility.
- Invert column selection option.
- Select duplicate rows added to rows menu.
- Virtual join behavior bullet TBD.
- A variety of new transforms are now in New Formula Column.
- Workflow Improvements
When JMP users stay “in the flow” of analysis, they make better decisions more quickly. High performance is a feature of JMP, and we’ve worked hard to modernize our code, test our algorithms with big data tables, and reduce bottlenecks to keep JMP running fast even with the most difficult data sets. And to make you more efficient, we’ve also focused on reducing the amount of time or number of clicks it takes to accomplish routine tasks in JMP.
Highlights
- Easily find the preference to be changed through preference searching and filtering.
- Updated scripting index with better search, and a compact mode that works well in a project.
- Preview results in Formula Editor before hitting OK.
- Better automatic sorting algorithm using natural sort. Lot 1, Lot 2 … Lot 10, Lot 11.
- Grouping of scripts in a data table.
- File quarantine alert to protect against unknown executable code within JMP files.
- Updated OpenGL View Settings dialog for easier customization any 3D graph.
- Multiple Factor Analysis
Multiple Factor Analysis (MFA) is a sensory analysis technique whose goals are to find groupings of products that are similar, as well as to identify outlier panelists – the panelists that are so different from the rest of the group that their values skew the results. MFA allows the researcher to perform a PCA-like analysis with untrained panelists. It is often used for pre-evaluation studies, where many different products are being tested, as well as with later-stage consumer panels where many consumers may rate the products without any training on standard sensory measurements.
Highlights
- Helps with sensory analysis.
- Identifies similar products and outlying panelists.
- Facilitates pre-evaluation studies, later-stage consumer panels and studies that have untrained panelists.
- DOE Additions
The DOE platform in JMP is world-class, better enabling users to solve challenging problems in a wide variety of real-word settings. In JMP 14, numerous improvements to the DOE features have been added.
Highlights
- A-optimality criterion added to Custom Design. This is useful if the optimal design needs to focus more heavily on certain effects rather than others. There isn't a natural way for D- or I-optimality to do this.
- Ability to design Balanced Incomplete Block Designs (BIBDs).
- Improvements to the way priors are specified when building Accelerated Life Test (ALT) Designs. ALT priors specified in a way most customers expect.
- In Compare Designs, up to 10 designs can now be compared through a JSL interface and up to five with the UI.
- Improvements to the Fit DSD algorithm and options that lets the platform find weakly quadratic terms and interactions that have weak heredity.
- Ability to right-click and create a data table from color map on correlations.
- Addition of pairwise incidence heatmap to MaxDiff designs.
- Improved space-filling over levels of a categorical factor.
- Option to create a run order column in Custom Design.
- CUSUM Control Chart and Quality Engineering Improvements
Quality engineers will find a variety of new diagnostics and time-saving tools in JMP 14. CUSUM charts now have the familiar look, feel and interpretation of traditional control charts, and the Control Chart Builder adds three-way control charts, so you can visualize both within- and between-group variability in the same report. The Process Capability platform adds new distributions and measures of variability, plus there is a new platform for managing spec limits.
Highlights
- CUSUM Control Chart platform added to the Quality Engineering menu.
- Three-way control charts in Control Chart Builder address within-group and between-group variation.
- Drift Detection, Goal Plot, three-way chart metric and numerous UI enhancements in Process Screening.
- Process capability: additional distributions, measures of variability and inclusion of the Process Performance Plot.
- New platform for managing spec limits.
- New Reliability Features
Modern reliability engineers must solve increasingly difficult problems while making products that are safe and reliable, and that protect the company’s brand in the market. Fulfilling the increasing needs of reliability engineers has been a priority for JMP and there have been many improvements to the reliability platforms in JMP 14.
Highlights
- Addition of Bayesian Inference for Fit Life by X.
- For parametric survival, the addition of a nested model tests in addition to graphical comparisons to match Fit Life by X.
- Addition of Bayesian analysis to ALT designs.
- Repairable System Simulation (RSS), cross component event/action links can be turned off with diagram operation option, which is useful for cleaning up a complicated diagram. Individual links can be viewed by selecting an action or event block to view relationship when cross component link option turned off.
- Improved Fit Censored JSL function to improve performance of Life Distribution with very large data sets containing Interval Censoring.
- New Probability plot of Standardized Residuals in Cumulative Damage.
- Added side-by-side comparison of fixed parameter results along with unconstrained results in the density profiler.
- Improved GUI for censor indicator in failure cause column for life distribution. This now works like censor with dropdown list.
- Recurrence analysis includes a calendar event plot, interarrival by age plot and save simulation command for the Non Homogenous Poisson Process models fit within the platform.
- Interface to Python
Python joins the suite of programming language interfaces in JMP, adding to the existing ability to connect to SAS, MATLAB and R. Engineers and scientists can now connect to Python, send data from JMP to Python, execute Python code and return results to JMP for data visualization, analysis and further exploration.
Highlights
- Connect to a local install of Python.
- Send data to Python.
- Execute Python code from a JSL script.
- Return data and results from Python programs.
- HTTP Request
When you have direct database access and an ODBC driver, you can easily query, join and filter data using Query Builder – but what about the many other rich data sources that you may access through APIs? With the new HTTP Request function in JSL, you can now write custom applications to communicate with external web servers. JSL also adds new JSON parsing functions to make it easier to get data from the web into JMP.
Highlights
- HTTP Request is a new, advanced JSL function that allows communication to web servers through APIs.
- JMP is now open to a rich set of data sources not accessible through the Query Builder and ODBC drivers.
- Suite of JSL commands for parsing JSON ease the task of getting this data into JMP.
- Improvements Sharing and Communication of Results
The best statistical discoveries are only realized when you can effectively share your results with decision makers. JMP 14 continues to add and enhance tools to share results with other JMP users by improving Dashboard Builder and by giving users more ways to share results with people who don’t have JMP.
Highlights
- Dashboard Builder adds easier-to-read drop zones, a blank dashboard template and the ability to store your own templates.
- Animated .gif recording and saving any place in JMP that there is a play button (Bubble plot, local data filter, column switcher for example) make it possible to embed a moving JMP visualization in a PPT slide, for example, without having to rely on Flash.
- The create web report functionality is a great way to organize and share the steps of an analysis project with an index page and links to interactive html reports. Create web report is now scriptable so the creation of the web report can be added to the end of a standard report script.
- Filter support in interactive html reports adds filtering through selection, but does not recalculate models, for example.
- Functional Data Explorer (JMP Pro)
Scientists and engineers are dealing with more and more data that is streaming from devices on the Internet of Things (IoT). These sensor streams come with a unique set of challenges. Hundreds or thousands of sensors streaming data create a large volume of data, very quickly. Devices like these are found in a variety of industries, including semiconductor, chemical and pharmaceutical manufacturing, and consumer packaged goods.
Whatever the industry, common problems exist: simplifying and cleaning up messy data, removing outliers, aligning curves, building surrogate models and creating features (for use as inputs, outputs or both) from sensor streams.
With Functional Data Explorer, a new platform in JMP Pro 14, you can quickly understand, clean up, align and build models from sensor streams or batch process data, and then easily output features to build predictive models with JMP Pro.
Highlights
- New JMP Pro platform for dealing with sensor/signal/streaming or batch process data.
- Clean up, align and conform data coming from sensors.
- Build surrogate models using a variety of techniques.
- Use output models and features in other predictive modeling platforms.
- New Features in Generalized Regression (JMP Pro)
Generalized regression (or GenReg) is the premier linear modeling platform in JMP Pro. With GenReg you can build models for many kinds of data. Some examples include DOE data, observational data, data with categorical responses, messy data, text data, highly correlated data, and more. In one place, you have a tool that fits models, selects variables, handles multicollinearity and provides diagnostic reports.
Highlights
- Additional distributions include more censoring (Gamma and exponential distributions add support).
- Multinomial response support (nominal responses with more than three levels).
- Additional selection techniques include best subset regression, backwards elimination, pruned forward selection and the Dantzig selection (which has gained popularity in the DOE community and is good for n<<p problems, liked supersatured designs).
- Other features include a reset solution button, VIFs, adjusted R-square, RMSE, QQ-Plots and F-tests. Finally, custom tests are supported, cross-validation support has been added for two-stage forward selection and the platform has been adjusted to perform faster with large and/or complex problems with many effects.
- General Modeling Improvements
There have been a number of improvements to the modeling platforms of JMP and JMP Pro to help users deal with a wider range of statistical analysis problems.
Highlights
- In Explore Missing Values, the addition of a new SVD/Matrix Completion-based approach that incorporates validation into the dimension reduction step and which scores new observations using the V matrix and a least squares estimate of the U for new rows of data. Explore Missing Values also support a validation column for imputation.
- Profiler Simulator: Addition of simulation for responses.
- Fit Least Squares: Addition of a residual quantile plot.
- Distribution platform: Addition of SHASH distribution.
- Fit Stepwise uses transforms instead of formula columns for saving terms for parts of categorical effects.
- Adjustment to the PCA algorithm using a sparse implementation that makes computing principal components much faster (even on non-sparse data). Also support for supplementary variables.
- Support multiple response columns as item columns in Association Analysis (JMP Pro) and Latent Class Analysis.
- K-NN and Naïve Bayes have profilers. K-NN adds a model selection to interactively pick K (JMP Pro).
- Formula Depot performance improvements, ability to publish recode columns, more model support, and support for derived columns (JMP Pro).
