Course ObjectiveAcquainting the student with numerical methods and applications to
Course ContentSeveral methods will be discussed for solving numerical problems in
econometrics. Topics include:
- floating point representation of numbers on computers
- numerical differentiation
- numerical integration: quadrature and Monte Carlo integration
- interpolation methods
- finding zeros of functions: bisection, Newton(-Raphson), Secant
- univariate optimization: golden section search.
- multivariate optimization: Newton(-Raphson) and BFGS with linesearch,
Nelder-Mead. Differential Evolution.
- optimization under restrictions using transformations.
- using optimization methods to compute Maximum Likelihood estimators in
non-Gaussian/non-linear econometric models
- Power method for computing eigenvalues and eigenvectors.
- Monte Carlo simulation methods
Teaching MethodsClasses and computer practicals.
Method of AssessmentIntermediate exam – Individual assessment
Final exam – Individual assessment
Assignment - Groups of 3-4 students
LiteratureCheney & Kincaid (2012), Numerical Mathematics and Computing. 7th
Recommended background knowledgeProgramming, Linear Algebra, Analysis II.
|Language of Tuition||English|
|Faculty||School of Business and Economics|
|Course Coordinator||dr. L.F. Hoogerheide|
|Examiner||dr. L.F. Hoogerheide|
dr. L.F. Hoogerheide
dr. A.A.N. Ridder
You need to register for this course yourself
|Teaching Methods||Study Group, Lecture, Computer lab|
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