Schedule.
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|
Thusday 14th |
Friday 15th |
|
Basic concepts of Time Series Analynis (stationarity, ARMA models and forecasting) |
9am to 12am |
9am to 12am |
|
2pm to 5pm |
2pm to 5pm |
|
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Monday 18th |
Tuesday 19th |
Wednesday 20th |
Thusday 21th |
Friday 22th |
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Adv. Time Series An. |
9am to 12am |
2pm to 5pm |
9am to 12am |
2pm to 5pm |
9am to 12am |
|
Geostatistics |
2pm to 5pm |
9am to 12am |
2pm to 5pm |
9am to 12am |
2pm to 5pm |
Program.
Advanced Time Series Analysis (Vincent Lefieux):
– Basic concepts of Time Series Analynis (stationarity, ARMA models and forecasting)
– Reminders on stationarity and ARMA models.
– Multivariate Time Series Analysis, including: VAR models, Cointegration, State-Space Model.
– Introduction to Spatial Time Series.
Geostatistics (Jean-Yves Dauxois):
– Spatial processes, Stationarity, Intrinsic Processes, Variogram, Models of Variogram, Statistical Inference.
– Kriging: Simple Kriging, Ordinary Kriging and Universal Kriging.
Prerequisites.
Probability.
Linear Models.
Inferential Statistics.
Basic concepts in Time Series Analysis.
Basic concepts in R software.
References.
Advanced Time Series Analysis:
– Hamilton, J.D. (1994). Time series analysis. Princeton University Press.
– Lütkepohl, H. (2005). New introduction to multiple time series analysis. Springer.
– Tsay, R.S. (2014). Multivariate time series analysis with R and financial applications. Wiley.
Geostatistics :
– Chilès, J.P. and P. Delfiner (1999). Geostatistics. Wiley, New York.
– Diggle, P.J. and Ribeiro, P.J. (2007). Model-based Geostatistics. Springer.
– Guyon, X. (1995). Random Field on a network. Springer, New York.
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