is there something like the curve fit platform where you can try different transformations of data to find the best linear fit?

[#1]

On the curve fit platform you can try different types of curves and see which one is the best fit.  I would like to be able to compare different data transformations to find the best linear fit. Is there a platform that can do this?

I am using JMP 17.0 on a MacBook Pro.

[#2]

Look at

     Analyze=>Specialized Modeling=>Fit Curve

Look for the documentation at here 

     Help=>JMP Documentation Library=>Predictive and Specialized Modeling

[#3]

but I only want a linear fit.  I want to try different data transformations to see which gives the best linear fit.

[#4]

An easy way to do that would be to create a separate new column for each of the transformations you want to use, and then use Fit Y by X platform and generate the Fit Line.  You can then order the different regressions by  Goodness of Fit

[#5]

I think you need to distinguish between linear functions and linear models.  Polynomials are nonlinear functions but are linear models - Y=f(X,X2, X3, etc.) can be a linear function.  Fit curve will fit such polynomials.  It will also fit things that are not linear models.  So, you can confine yourself to the polynomials for a start.  Now, if you want logarithmic transformations, then I think you will need to follow txnelson's advice and create columns for these.  Of course, a log transformation is a nonlinear function, but you can have a linear model in the logs of X and/or Y.  No platform will automatically cover all potential transformations.  I don't think you are insisting on only linear functions - least square regression will give you the best fitting linear function and there is no need to try others since the regression line (surface) is already the best fitting one.

[#6]

If you want to apply a Box Cox transformation before fitting the data, you can use the Fit Model  platform and in the red triangle menu select

Then go to the Box-Cox menu and select

and you will get a fit for the transformed variable:

[#7]

Graph Builder is also a great tool for fitting in a transformed coordinate system.
e.g. change the axis scale to log  - and fit a line instead of an exponential : )

there is a which which will bring such fits to a completely new level:
Graph Builder: disable Local Data Filter for specific plot types 

Besides log transform the user can also select differnet transforms like probit scale for normal distributions - or he can specify his own transformation "manually" via JSL / Scale to Internal/External. A nice example can be found in the scripting index:

[#8]

A third option: go to Fit Y by X and use Fit Special ...

In the menu you can pick some common transformations for X and Y axis:

[#9]

thanks!  this is the type of thing I was looking for.

[#10]

JMP provides an automated Box-Cox Transformation for the response in Fit Least Squares. This method generalizes the common transforms such as logarithms or roots.