Numerical Analysis
3rd Edition
ISBN: 9780134696454
Author: Sauer, Tim
Publisher: Pearson,
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Chapter 4.4, Problem 4CP
Let A be the matrix from Computer Problem 3, but with the diagonal elements replaced by
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Chapter 4 Solutions
Numerical Analysis
Ch. 4.1 - Solve the normal equations to find the least...Ch. 4.1 - Find the least squares solutions and RMSE of the...Ch. 4.1 - Find the least squares solution of the...Ch. 4.1 - Let mn, let A be the mn identity matrix (the...Ch. 4.1 - Prove that the 2-norm is a vector norm. You...Ch. 4.1 - Let A be an nn nonsingular matrix. (a) Prove that...Ch. 4.1 - Find the best line through the set of data points,...Ch. 4.1 - Find the best line through the set of data points,...Ch. 4.1 - Find the best parabola through each data point set...Ch. 4.1 - Find the best degree 3 polynomial through each set...
Ch. 4.1 - Assume that the height of a model rocket is...Ch. 4.1 - Given data points...Ch. 4.1 - Form the normal equations, and compute the least...Ch. 4.1 - Prob. 2CPCh. 4.1 - Prob. 3CPCh. 4.1 - Prob. 4CPCh. 4.1 - 5. A company test-markets a new soft drink in 22...Ch. 4.1 - What is the slope of the parabola y=x2on[ 0,1 ] ?...Ch. 4.1 - Find the least squares (a) line (b) parabola...Ch. 4.1 - Let A be the 10n matrix formed by the first n...Ch. 4.1 - Prob. 9CPCh. 4.1 - The following data, collected by U.S. Bureau of...Ch. 4.2 - Fit data to the periodic model...Ch. 4.2 - Fit the data to the periodic models...Ch. 4.2 - Fit data to the exponential model by using...Ch. 4.2 - Prob. 4ECh. 4.2 - Fit data to the power law model by using...Ch. 4.2 - Prob. 6ECh. 4.2 - Fit the monthly data for Japan 2003 oil...Ch. 4.2 - Prob. 2CPCh. 4.2 - Prob. 3CPCh. 4.2 - Prob. 4CPCh. 4.2 - Prob. 5CPCh. 4.2 - Prob. 6CPCh. 4.2 - Prob. 7CPCh. 4.2 - The file scrippsy. txt, available from the...Ch. 4.2 - The file scrippsm.txt, available from the textbook...Ch. 4.3 - Apply classical Gram-Schmidt orthogonalization to...Ch. 4.3 - Apply classical Gram-Schmidt orthogonalization to...Ch. 4.3 - Apply modified Gram--Schmidt orthogonalization to...Ch. 4.3 - Apply modified Gram-Schmidt orthogonalization to...Ch. 4.3 - Prob. 5ECh. 4.3 - Prob. 6ECh. 4.3 - Prob. 7ECh. 4.3 - Find the QR factorization and use it to solve the...Ch. 4.3 - Prove that a square matrix is orthogonal if and...Ch. 4.3 - Prove that the product of two orthogonal mm...Ch. 4.3 - Show that the Gram-Schmidt orthogonalization of an...Ch. 4.3 - Show that the Householder reflector method for the...Ch. 4.3 - Let P be the matrix defined in (4.29). Show (a)...Ch. 4.3 - Prob. 14ECh. 4.3 - Prob. 15ECh. 4.3 - Write a MATLAB program that implements the...Ch. 4.3 - Apply the classical Gram-Schmidt, modified...Ch. 4.3 - Prob. 3CPCh. 4.3 - Write a MATLAB program that implements (a)...Ch. 4.3 - Prob. 5CPCh. 4.3 - Use the MATLAB QR factorization to find the least...Ch. 4.3 - Prob. 7CPCh. 4.3 - Let x1,...,x11be11 be evenly spaced points in...Ch. 4.4 - Solve Ax=b for the following A and b=[ 1,0,0 ]T,...Ch. 4.4 - Prob. 2ECh. 4.4 - Let A=[ 10a1301a23001 ]. Prove that for any x0 and...Ch. 4.4 - Prob. 4ECh. 4.4 - Prob. 1CPCh. 4.4 - Prob. 2CPCh. 4.4 - Prob. 3CPCh. 4.4 - Let A be the matrix from Computer Problem 3, but...Ch. 4.4 - Prob. 5CPCh. 4.5 - The Gauss-Newton Method can be applied to find the...Ch. 4.5 - Prob. 2ECh. 4.5 - Prove that the distance from a point (x,y) to a...Ch. 4.5 - Prob. 4ECh. 4.5 - Find the matrix Dr needed for the application of...Ch. 4.5 - Prob. 6ECh. 4.5 - Prob. 7ECh. 4.5 - Prob. 1CPCh. 4.5 - Prob. 2CPCh. 4.5 - Prob. 3CPCh. 4.5 - Prob. 4CPCh. 4.5 - Prob. 5CPCh. 4.5 - Prob. 6CPCh. 4.5 - Prob. 7CPCh. 4.5 - Prob. 8CPCh. 4.5 - Prob. 9CPCh. 4.5 - Prob. 10CPCh. 4.5 - Prob. 11CPCh. 4.5 - Prob. 1SACh. 4.5 - Prob. 2SACh. 4.5 - Prob. 3SACh. 4.5 - Prob. 4SACh. 4.5 - Now repeat Step 4 with a more tightly grouped set...Ch. 4.5 - Decide whether the GPS en-or and condition number...
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- Spam filters are built on principles similar to those used in logistic regression. We fit a probability that each message is spam or not spam. We have several variables for each email. Here are a few: to_multiple=1 if there are multiple recipients, winner=1 if the word 'winner' appears in the subject line, format=1 if the email is poorly formatted, re_subj=1 if "re" appears in the subject line. A logistic model was fit to a dataset with the following output: Estimate SE Z Pr(>|Z|) (Intercept) -0.8161 0.086 -9.4895 0 to_multiple -2.5651 0.3052 -8.4047 0 winner 1.5801 0.3156 5.0067 0 format -0.1528 0.1136 -1.3451 0.1786 re_subj -2.8401 0.363 -7.824 0 (a) Write down the model using the coefficients from the model fit.log_odds(spam) = -0.8161 + -2.5651 + to_multiple + 1.5801 winner + -0.1528 format + -2.8401 re_subj(b) Suppose we have an observation where to_multiple=0, winner=1, format=0, and re_subj=0. What is the predicted probability that this message is spam?…arrow_forwardConsider an event X comprised of three outcomes whose probabilities are 9/18, 1/18,and 6/18. Compute the probability of the complement of the event. Question content area bottom Part 1 A.1/2 B.2/18 C.16/18 D.16/3arrow_forwardI need help making sure that I explain this part accutartly.arrow_forward
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