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Creating a prediction interval with monte carlo simulation

Hi,

 

I was wondering if anyone could help me.  

 

I have a set of data in two columns.  Column one contains a Run ID while Column 2 contains data generated by the run.  My end goal is to plot the 95% prediction interval of the confidence intervals produced by N, N-1, N-2, N-3... until you only have two datapoints per Run, where N = initial number of replicates.  Therefore step by step, If for example I had 40 replicates per run, I would like for JMP to randomly select 39 replicates for each run, conduct a lower 95% and upper 95% confidence interval for each Run, then conduct a lower 95% Prediction interval for the lower 95% confidence intervals of each run and a upper 95% prediction interval for the upper 95% confidence intervals of each run.  This would get repeated with 38 replicates, 37 replicates... until there is only 2 replicates.  I would like to graph on the x-axis the replicate number and plot both the upper 95% Preidiction interval and lower 95% prediction interval similar to what is shown below:

 

 

 

Re: Creating a prediction interval with monte carlo simulation

By the way, this solution makes use of bits of a script from an add-in presented at the JMP Discovery Summit Europe 2020.

Re: Creating a prediction interval with monte carlo simulation

Hi,

 

I believe I have an answer for you.  It makes use of the Bootstrapping functionality in JMP Pro, and for that reason will only work with JMP Pro.  Please take a look and let me know if it does what you are after.

 

Names Default To Here( 1 );
dt = Open( "$SAMPLE_DATA/Big Class.jmp" );

dist=dt<<DISTRIBUTION></DISTRIBUTION>