Here’s the problem. I have a list of ‘things’, for example, batch names. I can also get another list, for example, the start dates of the batches. How do I sort the batches by date? The answer: use the Rank Index function. (more…)
I’m going to take a look at the process of creating a JMP add-in to create a single-file deployment package for a collection of files associated with a JMP script. (more…)
There are two main classes of model for time series data – autoregressive (AR) and moving average (MA). The generalisation of the two is referred to as ARIMA – autoregressive integrated moving average. These models are sometimes referred to as Box-Jenkins models, but more accurately the term “Box-Jenkins” refers to a methodology for model selection. (more…)
Did you know that JMP has an LP Solver? Linear programming (LP) is a technique for optimising a function subject to a set of linear constraints. (more…)
As users of JMP Software we all develop our own opinions of what we like, what we don’t like, and how we think it should evolve.
So it’s very insightful to hear the perspective of the man behind the software – John Sall. He is hard to ignore, both physically (he is tall!) and intellectually (he is a giant!). But above all, he knows how we ought to be using the software whereas we just think we know. (more…)
This is the sixth and penultimate step in constructing the oneway advisor. The advisor automates four tests associated with the assumptions of a oneway analysis of variance. In this step a test will be performed to assess whether the data within each level of the grouping variable have equal variance. (more…)
In this step code will be developed to determine whether the residuals are normally distributed.
The advisor will validate the assumptions associated with a oneway analysis of variance. It is assumed that the user has created the oneway analysis prior to running the advisor. In this step this assumption is validated.