Monte Carlo methods
7.5 credits
The course contains:
•General generation of one-dimensional random numbers, discrete and continuous: the inverse method, the acceptance-rejection technique, the compositon approach
•Generating specific one-dimensional random numbers: normal random numbers by the polar method, Poisson random variables, binomial random variables
•Generation of Poisson processes: homogenous and nonhomogenous, one-dimensional and two-dimensional
•Generation of multidimensional normal random numbers
•Generation of variables from copula models
•Variancereductiontechniques:useantitheticvariablesandcontrolvari- ates, conditioning, stratigic sampling, non-normalized and normalized importance sampling, latin hypercube sampling
•Statistical analysis of simulated data: the sample mean and sample variance, interval estimates of a population mean, bootstrapping technique for estimating mean square errors
•Statistical validation techniques: goodness of fit tests
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Studying at a distance can be done in different ways, either entirely without physical gatherings or with only a few gatherings on campus or at one of our learning centres. The common denominator is that a large part of your studies takes place online. You communicate with the teacher and other students through a learning platform that includes discussion forums, opportunities for group work, and digital meetings. In many cases, you will also have access to recorded lectures via the learning platform.
The benefit of distance studies is the flexibility, something that is valuable if you want to be free to decide when and where you want to study. Some compulsory elements on you course or programme may take place during office hours, even though they are online.
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