M A Cau
Biographic Data
| ID | 5217649 |
|---|---|
| NAME | M A Cau |
| GIVEN NAMES | M A |
| FAMILY NAME | Cau |
| SIGNATURE | CAU M A |
| VERIFIED | No |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 30 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2001 |
| LATEST PUBLICATION YEAR | 2011 |
| H-INDEX | 3 |
Persistence of the cultural landscape in Campania (Southern Italy) before the AD 472 Vesuvius eruption
On Statistical Approaches to the Study of Ceramic Artefacts Using Geochemical and Petrographic Data
The scientific analysis of ceramics often has the aim of identifying groups of similar artefacts. Much published work focuses on analysis of data derived from geochemical or mineralogical techniques. The former is more likely to be subjected to quantitative statistical analysis. This paper examines some approaches to the statistical analysis of data arising from both kinds of techniques, including ‘mixed‐mode’ methods where both types of data are…
Model‐based Cluster Analysis of Artefact Compositional Data
Cluster analysis is the most widely used multivariate technique in archaeometry, with the majority of applications being exploratory in nature. Model‐based methods of clustering have their advocates, but have seen little application to archaeometric data. The paper investigates two such methods. They have potential advantages over exploratory techniques, if successful. Mixture maximum‐likelihood worked well using low‐dimensional lead isotope data…
Persistence of the cultural landscape in Campania (Southern Italy) before the AD 472 Vesuvius eruption
On Statistical Approaches to the Study of Ceramic Artefacts Using Geochemical and Petrographic Data
The scientific analysis of ceramics often has the aim of identifying groups of similar artefacts. Much published work focuses on analysis of data derived from geochemical or mineralogical techniques. The former is more likely to be subjected to quantitative statistical analysis. This paper examines some approaches to the statistical analysis of data arising from both kinds of techniques, including ‘mixed‐mode’ methods where both types of data are…
Model‐based Cluster Analysis of Artefact Compositional Data
Cluster analysis is the most widely used multivariate technique in archaeometry, with the majority of applications being exploratory in nature. Model‐based methods of clustering have their advocates, but have seen little application to archaeometric data. The paper investigates two such methods. They have potential advantages over exploratory techniques, if successful. Mixture maximum‐likelihood worked well using low‐dimensional lead isotope data…
Model‐based Cluster Analysis of Artefact Compositional Data
Cluster analysis is the most widely used multivariate technique in archaeometry, with the majority of applications being exploratory in nature. Model‐based methods of clustering have their advocates, but have seen little application to archaeometric data. The paper investigates two such methods. They have potential advantages over exploratory techniques, if successful. Mixture maximum‐likelihood worked well using low‐dimensional lead isotope data…
On Statistical Approaches to the Study of Ceramic Artefacts Using Geochemical and Petrographic Data
The scientific analysis of ceramics often has the aim of identifying groups of similar artefacts. Much published work focuses on analysis of data derived from geochemical or mineralogical techniques. The former is more likely to be subjected to quantitative statistical analysis. This paper examines some approaches to the statistical analysis of data arising from both kinds of techniques, including ‘mixed‐mode’ methods where both types of data are…
Persistence of the cultural landscape in Campania (Southern Italy) before the AD 472 Vesuvius eruption
Archaeology (3 works) · Archaeology and ancient environmental studies (3 works) · Geography (3 works) · Archaeological science (2 works) · Compositional data (2 works) · Computer Science (2 works) · Geochemistry and Geologic Mapping (2 works) · Geology (2 works) · Machine learning (2 works) · Mathematics (2 works)