Coming in JMP Pro 12: Variograms in Fit Mixed

In JMP Pro 11, we introduced the Fit Mixed platform for fitting models with a variety of covariance structures and random effects. With JMP Pro 12, we have improved on this platform, with noticeable changes coming to models with spatial covariance structures. These changes are detailed below. Enhanced speed Fitting […]

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Finding the best process operating conditions using 2 optimisation approaches

Scientists and engineers often need to find the best settings or operating conditions for their processes or products to maximise yield or performance. I will show you how the optimisation capabilities in JMP can help you work out the best settings to use. Somewhat surprisingly, the particular settings that are […]

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Coming in JMP 12: Probability and Multiple Choice Profilers in the Choice platform

The JMP Profiler is a powerful tool for visualizing your model. With one click, you can see what the model predicts when you change a product’s features or the adjust one of your assumptions. It’s also a powerful communication tool. Your audience doesn’t need a statistics background to understand the […]

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Coming in JMP 12: Interactive HTML Profiler

The Prediction Profiler, or simply Profiler, allows you to explore cross sections of predicted responses across multiple factors. It gives you a wealth of information about your model, and in JMP 12, you can export it to interactive HTML pages to share with others who do not have JMP. The Profiler […]

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Webcasts show how to build better statistical models

We have two upcoming webcasts on Building Better Models presented at times convenient for a UK audience: If you are new to JMP Pro, you will want to view the webcast on 21 October 2014. If you are already using JMP Pro, the webcast on 31 October 2014 will suit […]

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Alias Optimal versus D-optimal designs

In my previous blog entry, I discussed the purpose of the Alias Matrix in quantifying the potential bias in estimated effects due to the alias terms. In this blog post, we look at an example that creates a D-optimal design and an Alias Optimal design with the same number of […]

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What is an Alias Matrix?

When I create a design, the first place I typically look to evaluate the design is the Color Map On Correlations. Hopefully, I see a lot of blue, implying orthogonality between different terms. The Color Map On Correlations contains both the model terms and alias terms. If you have taken […]

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JMP Pro for linear mixed models — Part 3

This is the final post in my JMP for Linear Mixed Models series (see my earlier posts: Part 1 and Part 2). Here, I will show an example of spatial regression, followed by some tips for fitting mixed models in JMP Pro.  Example 4: Modeling geospatial data — taking spatial […]

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JMP Pro for linear mixed models — Part 2

In an earlier blog post, I introduced the new Mixed Model capability in JMP Pro 11 and showed an example of random coefficient models. In this post, I continue my discussion of using mixed models for repeated measures and panel data. I’ll leave modeling geospatial data as well as tips […]

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JMP Pro for linear mixed models — Part 1

JMP Pro 11 has added a new modeling personality, Mixed Model, to its Fit Model platform. What’s a mixed model? How does JMP Pro fit such a model? What are the key applications where mixed models can be applied? In this and future blog posts, I will try to dispel […]

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