Preprints

Filtering by Subject: Applied Statistics

Hierarchical Cluster Analysis by R language for Pattern Recognition in the Bathymetric Data Frame: a Case Study of the Mariana Trench, Pacific Ocean

Polina Lemenkova

Published: 2019-01-25
Subjects: Applied Statistics, Earth Sciences, Environmental Education, Environmental Monitoring, Environmental Sciences, Environmental Studies, Geographic Information Sciences, Geography, Geology, Geomorphology, Oceanography, Oceanography and Atmospheric Sciences and Meteorology, Other Earth Sciences, Other Oceanography and Atmospheric Sciences and Meteorology, Other Statistics and Probability, Physical and Environmental Geography, Physical Sciences and Mathematics, Social and Behavioral Sciences, Spatial Science, Statistics and Probability, Tectonics and Structure

The geographic focus of the current study Mariana trench, the deepest point of the Earth located in the west Pacific Ocean. Mariana trench has unique structure and features formed in the complex process of the trench development. There is a range of the environmental factors affecting trench structure and functioning: bathymetry, geography, geology and tectonics. Current research aimed to study [...]

Statistics and segmentation: Using Big Data to assess Cascades Arc compositional variability

Bradley William Pitcher, Adam J Kent

Published: 2018-09-24
Subjects: Applied Mathematics, Applied Statistics, Earth Sciences, Geochemistry, Geology, Multivariate Analysis, Physical Sciences and Mathematics, Statistics and Probability, Volcanology

Primitive lavas erupted in the Cascades arc of western North America demonstrate significant patterns of along-arc heterogeneity. Such compositional diversity may be the result of differences in mantle melting processes, subduction geometry, regional tectonics, or compositions of the slab, mantle or overlying lithosphere. Previous authors have partitioned the arc into four geochemically distinct [...]

Uncertainty in sea level rise projections due to the dependence between contributors

Dewi Le Bars

Published: 2018-03-08
Subjects: Applied Statistics, Climate, Earth Sciences, Environmental Sciences, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics, Probability, Statistical Models, Statistics and Probability

Sea level rises at an accelerating pace threatening coastal communities all over the world. In this context sea level projections are key tools to help risk mitigation and adaptation. Sea level projections are often made using models of the main contributors to sea level rise (e.g. thermal expansion, glaciers, ice sheets...). To obtain the total sea level these contributions are added, therefore [...]

Bootstrapped high quantile estimation --- An experiment with scarce precipitation data

Hung Tan Thai Nguyen, Harald Bernhard, Zhangsheng Lai

Published: 2018-02-25
Subjects: Applied Statistics, Physical Sciences and Mathematics, Probability, Statistics and Probability

This paper details team SUTD’s effort when participating in the “Prediction of extremal precipitation” challenge. We propose a framework that combines the generalized Pareto distribution, a bootstrap resampling scheme and inverse distance weights to capture spatial dependence. Our method reduces the quantile loss functions by 55.1% as compared to a naive benchmark, and shows improvement across [...]

Geostatistical modelling of cyclic and rhythmic facies architectures

Thomas Le Blévec, Olivier Dubrule, Cédric M. John, et al.

Published: 2017-11-07
Subjects: Applied Statistics, Earth Sciences, Physical Sciences and Mathematics, Sedimentology, Statistics and Probability

A pluri-Gaussian method is developed for facies variables in three dimensions to model vertical cyclicity, related to facies ordering, and rhythmicity. Cyclicity is generally characterized by shallowing or deepening-upward sequences and rhythmicity by a low range of variability in cycle thicknesses. Both of these aspects are commonly observed in shallow-marine carbonate successions, especially [...]

search

You can search by:

  • Title
  • Keywords
  • Author Name
  • Author Affiliation