- Docente: Saverio Ranciati
- Credits: 6
- SSD: MAT/06
- Language: Italian
- Teaching Mode: Traditional lectures
- Campus: Bologna
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Corso:
First cycle degree programme (L) in
Mathematics (cod. 8010)
Also valid for First cycle degree programme (L) in Statistical Sciences (cod. 8873)
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from Nov 06, 2023 to Dec 06, 2023
Course contents
Introduction to computational statistics and R programming.
Random Variable Generation. Uniform simulation, the inverse transform, general transformation methods, discrete distributions.
Monte Carlo Integration. Introduction, classical Monte Carlo integration. Importance sampling.
Monte Carlo Optimization. Introduction, numerical optimization methods, stochastic search (basic solutions, stochastic gradient methods, simulated annealing).
[Tentative] Bootstrapping. Introduction, parametric and nonparametric bootstrap.
Readings/Bibliography
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Robert, C. & Casella, G. (2010). Introducing Monte Carlo Methods with R. New York: Springer-Verlag.
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Efron, B. & Tibshirani, R. J. (1993). An introduction to the bootstrap. London: Chapman & Hall/CRC.
Teaching methods
• Conventional lectures
Assessment methods
The exame is comprised of a set of open questions and/or practical exercises to be solved using the software R.
The final mark of the "Numerical Analysis" course is defined as the arithmetic mean of the marks obtained in the test for the Numerical Analysis module and a written exam for the Computational Statistics module.
Teaching tools
Additional material provided by the teacher (iol.unibo.it)
Office hours
See the website of Saverio Ranciati