Hi,
Thanks for the reply. I did go through the manual. Still could not get what I was looking for.
I am now trying to script up this non-linear fitting and facing some issues. Need some help. Ill reiterate the problem here:
I have data which needs to be fit by a model which has 4 fit parameters. The fits for each category are NOT INDEPENDENT of each other. 2 of the fit parameters, B and beta as shown in above post need to be unique, i.e., the regression fit extracts a unique B and beta for all categories. While the other two parameters P and R0 can vary across categories.
The JMP interface looks something like shown below:
Now, I need to code this up in JSL.
I know we can do the below to get all four unique parameters:
dt << New Column("Model", Numeric, Continuous, Formula( Parameter( {B = 5, beta = 0.25, P = 10, R0 = 10}, R0 / (1 + B * (:Name( "tRelax(s)" ) / :Name( "tStress(s)" )) ^ beta) + P )));
However this is not what I want. And I don't want to using "grouping" feature as it would only help if the extractions were independent.
The code generated while I copy the formula is shown below:
Parameter(
{B = 2, beta = 0,
Name( "R0_Category_D03_01_-1.8_100" ) = 2,
Name( "R0_Category_D03_01_-1.8_1000" ) = 3,
Name( "R0_Category_D03_01_-1.8_10000" ) = 3,
Name( "R0_Category_D03_01_-1.8_158" ) = 3,
Name( "R0_Category_D03_01_-1.8_1580" ) = 3,
Name( "P_Category_D03_01_-1.8_100" ) = 0,
Name( "P_Category_D03_01_-1.8_1000" ) = 1,
Name( "P_Category_D03_01_-1.8_10000" ) = 1,
Name( "P_Category_D03_01_-1.8_158" ) = 0,
Name( "P_Category_D03_01_-1.8_251" ) = 0},
Exp( -B * (:Name( "tR" ) / :Name( "tS" )) ^ beta ) *
Match( :Category,
"D03_01_-1.8_100", Name( "R0_Category_D03_01_-1.8_100" ),
"D03_01_-1.8_1000", Name( "R0_Category_D03_01_-1.8_1000" ),
"D03_01_-1.8_10000", Name( "R0_Category_D03_01_-1.8_10000" ),
"D03_01_-1.8_158", Name( "R0_Category_D03_01_-1.8_158" ),
"D10_05_-2.6_6310", Name( "R0_Category_D10_05_-2.6_6310" )
) + Match( :Category,
"D03_01_-1.8_100", Name( "P_Category_D03_01_-1.8_100" ),
"D03_01_-1.8_1000", Name( "P_Category_D03_01_-1.8_1000" ),
"D03_01_-1.8_10000", Name( "P_Category_D03_01_-1.8_10000" ),
"D03_01_-1.8_158", Name( "P_Category_D03_01_-1.8_158" ),
"D10_05_-2.6_6310", Name( "P_Category_D10_05_-2.6_6310" )
)
)
I need to automate this and so cannot use this as is.
I can create arrays for P_XXX and R0_XXX from the column 'Category'.
I was thinking on the lines of creating associated arrays for each of these P and R0 and use them in formula, but did not work out.
Ofcourse after I create this formula, I need to run the non-linear regression fit on the column and data.
Can someone please help me code this?
Thanks
Binoy