- Computer Problem 3.1 of the text, p. 152. You can use Matlab's
built-in
**vander**and**polyval**to set up the least squares problems, but this is not necessary. If you want, you can use**fliplr**and**flipud**to make the notation of the Vandermonde matrix conform to the notation of the text, but this is not necessary either. You can use any method you like to solve the least squares problem; the easiest is Matlab's**\**. Please plot all the polynomial approximations on the**same**graph, for example using**hold on**. Collect the commands that do all this in a**function**, with comments, where the input to the function consists of the two data vectors**t**and**y**(don't assume they have length 6, but write the code more generally), and then call it for the data on p.152. - Write a
**function**to compute the least squares solution of**Ax ~ b**using the method of**Givens rotations**. You do**not**have to compute the matrix**Q**(the product of the Givens transformations), since you can apply the transformations to the right hand side**b**at the same time as they are applied to triangularize**A**. This is most easily done by collecting**A**and**b**into a single matrix and applying the transformations to both at once. Your function should not call the cosine or sine functions; it should use the formulas at the top of p.128 of the text. Also, don't put the Givens transformations into a matrix and multiply with it - this is much too expensive. Just apply the transformations to the individual rows of**[A b]**. Each Givens transformation involves replacing two rows by linear combinations of the same two rows, introducing a single zero in the desired position. When programming in Matlab, try to avoid loops as much as possible and use vector operations when you can. After applying all the necessary Givens transformations, the resulting matrix should be triangular, except for very small rounding errors where you expect 0's. You can set these to 0 (make sure they are tiny though!) before using**\**to solve the triangular system. Test your code on random matrices and compare it with what you get when you use a built-in method such as using**\**on the original data. If the least squares solutions do not agree to most digits on random examples, there is a bug in your code. - Computer problem 3.13 of the text, p.156, parts (a), (c), (d), (h)
only. For (d) use your function from the previous question; for the others,
you can use the built in
**chol, qr, svd**. As with the other questions, collect the commands that make the comparison inside a function; in this case the input parameter should be**epsilon**.