Giuseppe Arbia
Ente:
Università...
Struttura:
Dipartimento delle Scienze Aziendali, Statistiche, Tecnologiche ed Ambientali - Viale Pindaro, 42, 65127 Pescara
Qualifica:
Professore Ordinario
E-Mail: Arbia@unich.it
Elenco Pubblicazioni:
- G. Arbia (1993) The use of GIS in spatial surveys International. Statistical Review, 61, 2, Agosto, 339-359
- G. Arbia, P. Switzer (1994) Optimal step-wise spatial sampling designs Working paper, Universit di Padova, Dicembre 1994
- G. Arbia (1994) Selection techniques in sampling spatial untis Quaderni di statistica e matematica applicata alle scienze economico-sociali, Volume XVI, n. 1-2, Novembre 1994, pagg. 81-91.
- G. Arbia (1995) Updating existing sampling design in repeated environmental surveys Working Paper, Padova, N. 6. 1995
- G. Arbia, G. Lafratta G. e B. Scarpa (1996) Evaluating and updating the sample design for the concentration of SO2 in Padua Quaderni di Statistica n. 4/96, Dipartimento metodi quantitativi e teoria economica, Università G. d'Annunzio di Pescara
- G. Arbia, G. Espa (1997) Spatial sampling designs optimized under anisotropic superpopulation models Working paper, n. 5/97 Università G. d'Annunzio, Pescara
- G. Arbia, G. Lafratta (1997) Evaluating and updating the sample design: the case of the concentration of SO2 in Padua Journal of Agricultural, Biological and Environmental Statistics, Vol. 2, N. 4, 451-466
- G. Arbia (1999) A method-of moment procedure for estimating the spatial correlogram with sample data combined with remotely sensed information Atti SCO'99I, Venezia, 1999.
- G. Arbia, G. Espa (2001) Optimal spatial sampling strategies for agricultural and environmental data Proceedings of the Conference on agricultural and environmental statistical applications, Rome, 2001
- G. Arbia, G. Lafratta (2002) Spatial sampling design optimized under unisotropic superpopulation models Journal of the Royal Statistical Society series c - Applied Statistics, Vol. 51 Issue 2 Page 223-241
- G. Arbia, G. Lafratta (2006) Spatial sampling plans to monitor the 3-D spatial distribution of extremes in soil pollution surveys Computational Statistics and Data Analysis (submitted)