Module for Nonlinear Curve Fitting
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Data Linearization Method for
Exponential
Curve
Fitting. Fit
the curve
to
the data points
.
Taking the logarithm of both sides we obtain ![]()
, thus
.
Introduce the change of variable
. Then
the previous equation becomes
which is a linear equation in the variables X and Y.
Use the change of
variables
on
all the data points and obtain
for
.
Fit the points
with
a "least squares line" of the form
.
Comparing the equations
we
see that
. Thus
![]()
are used to construct the coefficients which are then used to "fit
the curve"
to the given data points
in
the xy-plane.
Example 1. Fit the
curve
to
the data points
.
Solution
1.
Data Linearization Method for a
Power
Function Curve
Fitting. Fit
the curve
to
the data points
.
Taking the logarithm of both sides we obtain ![]()
, thus
.
Introduce the change of variable
. Then
the previous equation becomes
which is a linear equation in the variables X and Y.
Use the change of
variables
on
all the data points and obtain
for
.
Fit the points
with
a "least squares line" of the form
.
Comparing the equations
we
see that
. Thus
![]()
are used to construct the coefficients which are then used to "fit
the curve"
to the given data points
in
the xy-plane.
Example 2. Fit the
curve
to
the data points
.
Solution
2.
Example 3. Often
times a scientist must decide which formula "fits" the
data best.
3(a). Find both the
"exponential fit" and "power fit" for the data
points
.
3(b). Discuss how this
was accomplished and what transformations were used in the
process.
3(c). Determine which
curve fits the data best.
Solution
3.
Old Lab Project (Nonlinear
Curve Fitting Nonlinear
Curve
Fitting). Internet
hyperlinks to an old lab project.
Research Experience for Undergraduates
Nonlinear
Curve Fitting Nonlinear
Curve Fitting Internet hyperlinks to web
sites and a bibliography of articles.
Downloads (Nonlinear
Curve Fitting Nonlinear
Curve
Fitting).
Download this Mathematica notebook.
(c) John H. Mathews 2003