# EGR 103/Fitting

## Contents

## Palm Problem 6.10

This is pretty straightforward - just figure out a smart way to keep track of three sets of coefficients and three sets of statistics. Use both the numbers and the graphs to form your conclusions about the usefulness of additional terms.

## Chapra Problem 15.7

This is a multidimensional linear fit. Don't forget to calculate the required estimate and error in that estimate!

## Chapra 15.11

This is a nonlinear fit. Don't forget to justify your choice of initial conditions!

## Chapra 14.11 (Linearized)

The key here is to write the program for one fit (say, exponential) and get everything working perfectly for it. Choose some smart way of naming the variables so that you know what fit they are for. Then, once you are happy with how the exponential part is working, determine what code to copy in each section for the power law. Once *that* is working the way you like, copy the code for saturation growth model. The code will end up being fairly long (three models to calculate, plus six figures to make). But quite a bit is build from previous code.

## Chapra 14.11 (Nonlinear Regression)

The smart thing to do here is recognize that the only difference between this code and the previous code will be in generating the coefficients for the model. Take the program above, clearly identify where you need to pull out the linearized code and put in nonlinear regression. You will also need to change the file names of the figures.

## Notes

By the end of this lab, you will have programs that can do multiple orders of polynomial fits, multidimensional fits, linearized fits, and nonlinear fits. That represents a pretty impressive set of abilities!