CS/SE 4X03 Final Examination DAY CLASS DURATION OF EXAMINATION: 2 hours MCMASTER UNIVERSITY FINAL EXAMINATION Special Instructions: 1. You must not communicate with anybody during this exam. 2. You must not use the Internet. 3. You can use Matlab or a calculator. 4. Textbooks are allowed. 5. Write your solutions in the space provided in […]
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CS/SE Eng 4X03 Do Not Share this document Problem 1 [4 points] Let x and y be finite IEEE-754 double precision numbers. Consider the evaluation of u = x*sqrt(y); v = 2*u; in IEEE double precision (sqrt is the square root fuction). Assume no overflows or underflows occur in this evaluation. Derive a bound for
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Economics 406 – Winter 2022 Data Project The data project is worth 20% of your grade. It is due on April 14, 2022. There is a dropbox where you can submit your executive summary and all your codes and output. 1 Description of the project This data project uses an SVAR to analyze the impact
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Nonlinear Econometrics for Finance Lecture 1 . Econometrics for Finance Lecture 1 1 / 42 Welcome to Copyright By PowCoder代写 加微信 powcoder Nonlinear Econometrics for Finance! . Econometrics for Finance Lecture 1 2 / 42 The course in a nutshell 1 You are used (from Linear Econometrics for Finance) to estimating models written as follows:
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Nonlinear Econometrics for Finance Lecture 2 . Econometrics for Finance Lecture 2 1 / 26 Asset Pricing Copyright By PowCoder代写 加微信 powcoder Last class: Asset Pricing Contrary to Lecture 1, the risk-less rate Rf is not zero In general, all asset pricing models imply the following equivalence: pt = Et[mt+1xt+1] = 1 EQt [xt+1],
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INTRODUCTION TO MATLAB FOR ENGINEERING STUDENTS David Houcque Northwestern University (version 1.2, August 2005) Contents 1 Tutorial lessons 1 1 1.1 Introduction……………………………… 1 1.2 Basicfeatures…………………………….. 2 1.3 AminimumMATLABsession…………………….. 2 1.3.1 StartingMATLAB ………………………. 2 1.3.2 UsingMATLABasacalculator ………………… 4 1.3.3 QuittingMATLAB………………………. 5 1.4 Gettingstarted ……………………………. 5 1.4.1 CreatingMATLABvariables………………….. 5 1.4.2 Overwritingvariable ……………………… 6 1.4.3 Errormessages ………………………… 6
Linear Algebra in Twenty Five Lectures Tom Denton and Andrew Waldron March 27, 2012 Edited by Katrina Glaeser, Rohit Thomas & Travis Scrimshaw 1 Contents 1 What is Linear Algebra? 12 2 Gaussian Elimination 19 2.1 NotationforLinearSystems ………………. 19 2.2 ReducedRowEchelonForm ………………. 21 3 Elementary Row Operations 27 4 Solution Sets for Systems of Linear
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Convex Optimization Convex Optimization Stephen Boyd Department of Electrical Engineering Stanford University Lieven Vandenberghe Electrical Engineering Department University of California, Los Angeles cambridge university press Cambridge, New York, Melbourne, Madrid, Cape Town, Singapore, S ̃ao Paolo, Delhi Cambridge University Press The Edinburgh Building, Cambridge, CB2 8RU, UK Published in the United States of America by
A tutorial on Principal Components Analysis Lindsay I Smith February 26, 2002 Chapter 1 Introduction This tutorial is designed to give the reader an understanding of Principal Components Analysis (PCA). PCA is a useful statistical technique that has found application in fields such as face recognition and image compression, and is a common technique for
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Nonlinear econometrics for finance HOMEWORK 3 GMM, MLE and Volatility This homework consists of three problems. • The first problem uses the same data as in Assignment 1 (housing data.xslx). You will estimate the parameters of the linear regression model using Copyright By PowCoder代写 加微信 powcoder the least-squares (LS) estimator (like in the first assignment),
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