Daniel Mandallaz
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Daniel Mandallaz is a senior scientist and lecturer in forest biometry at the Chair of Land Use Engineering. Daniel is born in 1951 in Annecy (Savoy, France). He obtained his High School Leaving Certificate in 1970 in Geneva, his Diploma in mathematics at ETH in 1975 and his MSc in statistics at Imperial College, London, in 1976. From 1977 until 1981 he worked as a statistician at Ciba-Geigy (now Novartis) in Basel, and from 1981 as Head of medical statistics for Shering Plough, European Headquarter, in Lucerne. 1983 he returned as senior assistant to ETH, where he obtained his PhD in forest Biometry in 1991 and his Habilitation in geostatistics in 1993. From 1991-2012 he was also a lecturer in mathematics at the University of Applied Sciences in Zurich and from 1997-2012 a lecturer in biostatistics at the University of Zurich. Daniel is the author of several papers in forest biometry and biostatistics. His book “Sampling Techniques for Forest Inventories” (2008, Chapman and Hall) is regarded as a reference. Daniel is married and has one daughter who preferred to become an architect.
Publikationen vor 2004
MANDALLAZ D. (2003): Die Antizipierte Varianz: ein Werkzeug für die Optimierung von Waldinventuren. Schweizerische Zeitschrift für das Forstwesen. 154 (3): 117-121.
MANDALLAZ D. (2002): Optimal sampling schemes based on the anticipated variance with lack of fit. Canadian Journal of Forest Research. 32 (12): 2236-2243.
MANDALLAZ D., BACHMANN P., and DVORAK L. (2001): Sturmschäden in ungleichförmigen Beständen. Schweizerische Zeitschrift für das Forstwesen. 152 (11): 445-452.
MANDALLAZ D., LANZ A. (2001): Further results for optimal sampling schemes based on the anticipated variance. Canadian Journal of Forest Research. 31 (10): 1845-1853.
MANDALLAZ D. (2000): Estimation of the spatial covariance in Universal Kriging: Application to forest inventory. Environmental and Ecological Statistics. 7 (3): 263-284.
MANDALLAZ D., YE R. (1999): Forest inventory with optimal two-phase two-stage sampling schemes based on the anticipated variance. Canadian Journal of Forest Research. 29 (11): 1691-1708.
MANDALLAZ D., YE R. (1997): Prediction of forest fires with Poisson models. Canadian Journal of Forest Research. 27 (10): 1685-1694.
MANDALLAZ D. (1995): Le hasard fait bien les choses. Schweizerische Zeitschrift für das Forstwesen. 146 (12): 1015-1032. (Gekürzte Fassung der Antrittsvorlesung vom 14.11.1994 an der ETH Zürich).
MANDALLAZ D., BACHMANN P. (1995): Landesinventar als Informationsbasis für die Waldentwicklungsplanung. Schweizerische Zeitschrift für das Forstwesen. 146 (12): 981-990.
MANDALLAZ D. (1993): Geostatistical methods for double sampling schemes: applications to combined forest inventory, 133p. http://e-collection.library.ethz.ch 133 p.
MANDALLAZ D. (1991): A unified approach to sampling theory for forest inventory based on infinite population models, 255p. http://e-collection.library.ethz.ch
MANDALLAZ D., SCHLAEPFER R., and ARNOULD J. (1987): Dépérissement des forêts: échantillonnage simples ou par satellites? Schweizerische Zeitschrift für das Forstwesen. 138 (4): 277-292.
MANDALLAZ D., AMACHER M. (1986): Stochastic versions of Lancaster equations in Wargaming. European Journal of Operational Research. 24 (1): 41-45.
MANDALLAZ D., SCHLAEPFER R., and ARNOULD J. (1986): Forest damage-attempt to model relationships. Annales des Sciences Forestières. 43 (4): 441-458.
SCHÜTZ J.P., MANDALLAZ D., GRUNDER K. (1986): Vigor of Silver fir and how it is affected by stand structure, growth and yield, plant nutritional and silvcultural characteristics. Forstwissenschaftliches Zentralblatt. 105 (5): 406-420.
MANDALLAZ D., FLÜHLER H. (1983): Bayesian approach to bioequivalence-an example. Journal of pharmaceutical sciences. 72 (10): 1178-1181.
MANDALLAZ D., MAU J. (1981): Comparison of different methods for decision-making in bio-equivalence assessment. Biometrics. 37 (2): 213-222.
Technical reports in the ETH Library
Available on-line at: http://e-collection.library.ethz.ch
D. Mandallaz (1991): A unified approach to sampling theory for forest inventory based on infinite population and superpopulation models, PhD Thesis, 256p.
D. Mandallaz (1993): Geostatistical methods for double sampling schemes: applications to combined forest inventories, Habilitation Thesis, 133p.
D. Mandallaz (1997): The anticipated variance: a tool for the optimization of forest inventories, 73p.
D. Mandallaz (2001): Optimal sampling schemes based on the anticipated variance with lack of fit, 59p.