JMP Wish List

Hi  Would it be possible to get a native propensity score matching app in jmp like we have in SAS . It could be quite helpful for us clinicians .    thanks sajid ... View more

*Edit* might be a duplicate of JSL to JSON    I put in a post, then realized it should probably be a wish list item.   I'm trying to put a jmp data table (any jmp data table) into a database and query something like "What are the units of :height in "Big Class" I uploaded yesterday?"   So I'd love it if there was a way to go from data table to JSON and back.  Like <<GetScript(); Something like    Names default to here( 1 ); dt = open("$SAMPLE_DATA\Big Class.jmp"); json = dt << GetJSON(); dt_copy = ParseJSON(json);   ... View more

The Multivariate platform does only accept one input list. Once the dialog is run, correlations will be calculated on all pairwise X from the input list. Similarly when adding a Scatterplot to the multivariate analysis, all pairwise scatterplots will be shown. However, in many situations there is an interest in only "correlating" and creating a scatterplot on a certain list of X variables versus another list of X (or Y) variables in terms of exploratory data analysis. Since all variables are always there this is a tedious task to scroll through that massive matrix of scatterplots in scenarios of wide datasets. I'd appreciate to see two input lists for Multivariate with pairwise correlations/scatterplots from the variables in one list versus the variables in the other list. ... View more

We import text files all the time that have a variable number of comment lines at the top starting with "#".   Please add a way for JMP to ignore these lines when importing text files so we don't have to pre-process them.   Even better if there were a way to read the column names out of the line that starts with a given string, e.g. "#n". ... View more

Dear JMP Team,   I'd love to have the ability to generate a summary table where the data itself was linked to the source table. And if I'm being greedy, I'd like to be able to use the summary table to generate a table of stacked columns which also link back to the original source table. This would ultimately result in the ability to change the source data and have the change reflected in a stacked summary table.   Thanks,   Kevin Herlihy ... View more

1) I would like to suggest adding the option to bootstrap to the validation process in the platforms. Either as a validation option directly (i.e. as one more alternative to the existing K-fold, holdout, etc), or as a nested option i.e.bootstrap the holdout or K-folds. In my mind it is more intuitive and makes sense from a workflow perspective. Also, if one bootstraps at the end by  right-clicking results, one gets the bootstrap only of a specific table and not the whole model's estimates i.e. if I bootstrap a table, I get the table results but not the results from the residuals or diagnostics etc. Moreover, the resulting table is raw and unprocessed and lacks context; it is also more involved to use those results to assess and improve the model. If I bootstrap  a model I would then need to take those results and further work with them to integrate the results into my analytical process and decision making. Having the bootstrap integrated into the modeling platform would include the bootstrapped estimates and results for the whole model as separate table results. It would leverage the bootstrapping option to really use it for improving modeling (better models, more analytics on their performance and stability, etc).   2) Related to that is adding the option to bootstrap every model fit in the platform. For example logistic fits don't have validation, and using the bootstrap with the output table is very onerous to the point of being useless for a user that doesn't know scripting and stats theory to high level. Adding the option to bootstrap to the platform would make it much easier to manage. Nowadays doing validation is standard for almost any fit where there is a significant number of predictors, regardless of the fit platform used.   Uriel. ... View more

I'd like to have a multivariate x axis in the Fit Y by X platform, with the ability to run Means testing. I use the Variability chart in the variability gauge platform to show how multiple (non-continuous) variables grouped on the X axis impact a Y numeric product response. I'd like to be able to run means ANOVA testing for each of the variables plotted on the X-Axis.  ... View more

I wish different lines on a x-y plot in Graph builder would appear with different symbols in addition to different colors, by default.  The reason by default is important is because, as someone who is slightly (very?) color blind, I find it difficult to differentiate between the different overlay categories simply based on color.  Often I'll manually change symbols in the dataset one by one in order to see the differences. ... View more

Hello:   Can we have JMP16 do ensemble clustering (clustering of cluster solutions). One possible implementation is in R package CLUE.  My input variables are cluster solutions (hierarchical 3 clusters, hierarchical 4 clusters, K-means 3 clusters, K-means 4 clusters, Normal mixtures 2 clusters, and so on).  Research has shown ensemble clustering capitalizes on all the different solutions and produces more stable clusters.   A thought is to use LCA on these categorical variables, but it imposes a latent class model. We need a consensus solution.  How to do this in JMP other than an R integration?   Thanks ... View more

When using query builder the data type "datetime2" implements a character rather than a date and time. This format seems to be gaining in popularity as it adds more granularity but the only solution to get it to date time format correctly currently requires custom sql queries. My suggestion is to have "datetime" and "datetime2" both have a date and time format.      ... View more

It looks like the interface between a python dataframe and a jmp datatable goes through a csv file. Is that true? For example:   Python Init(Path("C:\Program Files (x86)\Microsoft Visual Studio\Shared\Python37_64\python37.dll")); Python Submit( "\[import pandas as pd df = pd.read_parquet('c:/temp/tst.parquet') ]\" ); dt = Python Get(df); // this method is saving the df as csv and then opens it in jmp. Is there a way to do that in memory dt << New Data View; Python Term();   In the above code I see JMP opening a progress bar for reading a csv during the Python Get(df) call. This is taking a very long time in large files. We would like a way to import the data-frame to data-table w/o the time to save as csv and reading it ... View more

As a clinician researcher in translational science, I love JMPs ease of use and powerful features, visualization, etc. But there are features that would make it more useful for multi-omics data: 1) support/help/guidance/platforms that focus on small sample sizes with lots of data (i.e. your typical medical basic research where the number of patients is limited but the number of variables per patient is large). A commonly used algorithm that is missing is OPLS-DA, which granted is just an application of PLS-DA which JMP has. You do have lasso which is also popular. Implementing other neural network/machine learning algorithms would be great (XGBoost!). But the point is to integrate the different options into an add-in or platform specific for these tasks, and the guidance/help associated. 2) Support for longitudinal sampling: many times the patients are sampled more than once. Adding that to the above would make JMP stand out and lead the field for these types of analyses. 3) variable selection is crucial, and using different ways is important to see how they perform, i.e. forward addition or backward elimination, bootstrapping (to maintain the #of predictors per variable) vs sub-sampling, etc. Having a profiler for this type of analyses would be amazing, or having a learning curve simulation that shows how the models are expected to perform for given parameters used. 4) The associated visualizations and model comparison and choosing.  5) Another very important feature is network analysis. I don't mean the neural/ML versions, but the ones that use correlations between different variables to create their maps of associations. It's like doing the SEM in the reverse direction. This would be especially useful if done at the individual level i.e. take every patient's scatterplot matrix, and look at the same pairs accross all patients to see which variables are consistently correlated. This is different than putting all the point from all the patients together in one big sample.     Perhaps some of these features exist in separate parts of JMP, and I guess some could be automated/recreated using JSL. But for those of us who are drawn to JMP because it is not R, then having these features organized coherently like other JMP platforms would make a big difference. I can also say that this is the same problem with all the other leading commercial stats packages, so a robust implementation in JMP would be a differentiator.  ... View more

It would be wonderful, if the layout design in journals were freely configurable. e.g. by using free movable boxes that contain the analysis,  data and graphics - almost like desktop publishing. Being able to make flexible designs in journals, they would easier fit to corporate design requirements.   ... View more

I would like to be able to get Expected Counts and Contributions to the Chi Square for Goodness of Fit tests like I can get with the Two Way Tables.  I teach statistics in the General Curriculum and I have to generate output using Minitab for that portion of the curriculum to have my students do problems.     I will never convince my colleagues to teach with JMP if it's not as easy as what they already do with Minitab.   ... View more

I would like to be able to get z-intervals for the proportion and test hypotheses about the one and two proportions as easily as I can get CI and test hypotheses about one and two means.     While the add ins do the job, I will never convince my colleagues to use JMP if it's not as easy as what they already do with Minitab.   ... View more

I would like a built-in function similar to Col Moving Average() that computes a moving (rolling) quantile of a a column. You could call it Col Moving Quantile() and/or Col Moving Median(). I wrote a user function (attached) which works well enough for small tables, but it uses a very inefficient approach. I know for absolutely sure that there are much more efficient ways to implement this function that don't involve brute force recalculation at each rolling step. Those approaches are beyond my coding ability. Add Custom Functions( New Custom Function( "x", "Col Moving Quantile", Function( {col, p, before, after, dt = Current Data Table()}, {coldata = Column( dt, col ) << Get As Matrix, from = Max( Row() - before, 1 ), to, to = Min( Row() + after, N Rows( dt ) )}, Quantile( p, coldata[Index( from, to )] ) ) ) // === Documentation === <<Formula Category( "Statistical" ) // <<Scripting Index Category( "Statistical+" ) // <<Description( "Returns the moving (rolling) quantile of the specified column." ) // <<Prototype( "x:Col Moving Quantile( ColName( string ), p, before, after, <Table reference> )" ) // <<Parameter( "String", "ColName( string )" ) // <<Parameter( "Number", "p" ) // <<Parameter( "Number", "Before" ) // <<Parameter( "Number", "After" ) // <<Parameter( "Name", "Table" ) );   ... View more

I plead that all import filters in the Open function get an option to import everything into character columns. This way, a jsl developer can control data formats in columns and not rely on luck that JMP guesses the types right - which is often not the case. Also, such an option should be really easy to implement and it will remove a lot of PAIN :) ... View more

This is more of a SAS wish list   JMP SaveAs SAS Dataset can save JMP column properties in the SAS Dataset Extended attributes Create a SAS Macro that will read these extended attributes, create and apply a user format from the JMP Value Labels.  ... View more

Option to use rowstate column in platforms instead of table rowstate   The table rowstate is good for hiding and excluding observations in an analysis. Unfortunately, the table rowstate is too easily changed. You can preserve rowstates in a rowstate column, but you then either have to replace the table rowstate or resort to JSL coding to use the rowstate column.   ... View more