# 3.146 FAQ-884 How to get a good fit with a very large or a very small parameter?

Last Update: 9/21/2017

When you do curve fitting, you might meet these problems:

• Origin returns missing value in standard errors when you perform fitting with a large parameter.
• Fit can not converge when you perform fitting with a very small parameter.

In both cases, we need to redefine the equations to avoid a very large or a very small parameter. For example:

• $y = A \cdot x$; if A is a large parameter, we can redefine the equation as $y=(A' \cdot 1E3) \cdot x$. After fitting, we can get $A = A'\cdot 1E3$;
• $y = A \cdot x$; if A is a small parameter, we can redefine the equation as $y=(A' \cdot 1E-3) \cdot x$. After fitting, we can get $A = A' \cdot 1E-3$;

Another actual example is the nonlinear implicit diode function:

$f = Is \cdot {e^{(\frac{{V - I \cdot Rs}}{{k \cdot T}} - 1)}} + \frac{{V - I \cdot Rs}}{{Rsh}} - I\,\!$, k is in $eV{K^{ - 1}}\,\!$ as a unit.

To do fitting with this function, firstly, we can reset the parameter $Is$ to $I's$, where $I's=Is*exp(-20)$, then the parameter $I's$ won't be too small.

$f = I's \cdot [{e^{(\frac{{V - I \cdot Rs}}{{k \cdot T}} - 20)}} - {e^{ (- 20)}}] + \frac{{V - I \cdot Rs}}{{Rsh}} - I\,\!$

In this way, we can avoid the very small parameter and finally get the fit converge.

Keywords:good fit, not converge, missing value in standard error,diode function