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Winter School - Bibliography

Time Series Analysis Books

 Box, G. E. P., and Jenkins, G. M. (1976). Time Series Analysis: Forecasting and Control, Holden-Day, San Francisco, CA .

 Hipel, K. W., and McLoad, A. I. (1994). Time Series Modelling of Water Resources and Enviromental Systems, Elsevier Publishers, The .

 Chow, V. T., Maidment, D. R. and Mays, L. W. (1988). Applied Hydrology, McGraw-Hill Series on Water Resources, New York . PDF Chapters 11,12.

 

Long Memory Correlation and Fractal Books

 Beran, J. (1994). Statistics for Long-Memory Processes, Chapman and Hall, New York, NY . PDF.

 Feder, J. (1990). Fractals, Plenum Publishers, New York, NY .

 

Statistical Hydrology and Statistic Books

 Bras, R. L., and Rodriguez-Iturbe, I. (1985). Random Function and Hydrology, Dover Publications, New York, NY . PDF1. PDF2.

 Kottegoda, N. T., (1980). Stochastic Water Resources Technology, Macmillan, New York , NY. 

 Mood, A. M., Graybill, F. A., Boes, D.C. (1983). Introduction to Statistics, McGraw-Hill, New York , NY.

 

Instructor Publications on Time Series Analysis and Segmentation Procedure

  Grimaldi, S. (2004). “Linear parametric models applied on daily hydrological series”, Journal of Hydrologic Engineering, 9(5): 383-391. PDF.

 Grimaldi, S., Tallerini, C., Serinaldi, F. (2005). “Multivariate linear parametric models applied to daily rainfall series”, Advances in Geosciences, 2: 87-92. PDF.

 Ferrante, M., Grimaldi, S., Napolitano, F., Ubertini, L., (2001).“Daily rainfall simulation procedure with parametric models”, IASTED Conference. Pittsburgh, .

 Grimaldi, S., Napolitano, F. and Ubertini, L. (2005).  “A procedure to use linear parametric models for daily rainfall series estimation.”, To be submitted. PDF.

 Hubert P. (2000) The segmentation procedure as a tool for discrete modeling of hydrometeorological regimes, Stochastic Environmental Research and Risk Assessment, 14, pp 297-304. PDF

Kundzewicz Z.W., Robson A. Editors (2000) Detecting trend and other changes in hydrological data, World Climate Programme - Data and Monitoring, WMO, Geneva, 113-119. PDF

 Other Publications on Time Series Analysis

 Montanari, A., Rosso, R., Taqqu, M.S. (1997). “Fractionally differenced ARIMA models applied to hydrologic time series: Identification, estimation, and simulation”, Water Resources Research, 33(5): 1035-1044. PDF.

 Higuchi, T. (1988). “Approach to irregular time series on the basis of the fractal theory”, Physica, D, 31: 277-283. PDF.

 Taqqu, M.S., Teverovsky, V. (1998). “On estimating the intensity of long-range dependence in finite and infinite variance time series”, In: A Practical Guide to Heavy Tails: Statistical Techniques and Applications. Adler, R., Feldman R. and M.S. Taqqu, eds, Birkhauser, Boston , 177-217. PDF.

 Taqqu, M.S., Teverovsky, V. (1997). “Robustness of Whittle-type estimators for time series with long range dependence”,  Stochastic Models. PDF.

 PhD Thesis, in Italian, Salvatore Grimaldi

 

 

 

 

 

 

 

  

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

ex facoltà di Agraria - Università degli studi della Tuscia (Viterbo)