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Jul 15, 2017 4:26 PM
(475 views)

I am performing a nonlinear anlysis (Specialized modeling, nonlinear) on a large plant growth dataset made up of hundreds of types of plant. In the nonlinear platform, the Y is plant size, the X is time, and I want to do this analysis "By" plant type. This leads to hundreds of "fit curve" boxes in which I would have to specify further anlalyses. Instead, I would like to automate this process, by fitting the peak model "fit gaussian peak" in every case. I would then create a combined table with all of the (hundreds) of estimated parameter values.

Can anyone please advise on whether I can automate this process to run hundreds of "fit gaussian peak" models at the same time?

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Jul 16, 2017 11:22 AM
(881 views)

Solution

Here is the same example, but with a "By" clause. All of this is available in the Scripting Index.

Help==>Scripting Index==>Fit Curve

The Scripting Index and the Scripting Guide are the definitive publications that contain the definative information on JSL.

```
Fit Curve( Y( :height ), X( :weight ),
Fit Gaussian Peak,
by(:sex)
);
```

Jim

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Jul 15, 2017 5:09 PM
(469 views)

You need to run your analysis interactively and then save the script, and you will get the code to Fit Gaussian Peak

`Fit Curve( Y( :height ), X( :weight ), Fit Gaussian Peak );`

Jim

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Jul 16, 2017 12:27 AM
(460 views)

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Jul 16, 2017 11:22 AM
(882 views)

Here is the same example, but with a "By" clause. All of this is available in the Scripting Index.

Help==>Scripting Index==>Fit Curve

The Scripting Index and the Scripting Guide are the definitive publications that contain the definative information on JSL.

```
Fit Curve( Y( :height ), X( :weight ),
Fit Gaussian Peak,
by(:sex)
);
```

Jim

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Jul 17, 2017 4:01 AM
(428 views)

And (building on Jim's example) you can get the parameter estimates into a table like this:

```
NamesDefaultToHere(1);
dt = Open("$SAMPLE_DATA/Big Class.jmp");
fc = dt << Fit Curve( Y( :height ), X( :weight ), Fit Gaussian Peak, by(:sex));
// Get all the parameter estimates into a single table
firstRep = Report(fc[1]);
dt2 = firstRep[TableBox(3)] << makeCombinedDataTable;
dt2 << setName("Parameter Estimates from "||(dt << getName));
```