Spatio-temporal modelling for non-stationary point referenced data

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Title

Spatio-temporal modelling for non-stationary point referenced data

Content partner

Victoria University of Wellington

Collection

Open Access Victoria University of Wellington

Description

<b>Spatial and spatio-temporal phenomena are commonly modelled as Gaussian processes via the geostatistical model (Gelfand & Banerjee, 2017). In the geostatistical model the spatial dependence structure is modelled using covariance functions. Most commonly, the covariance functions impose an assumption of spatial stationarity on the process. That means the covariance between observations at particular locations depends only on the distance between the locations (Banerjee et al., 2014). It has...

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Format

Research paper

Research format

Scholarly text / Thesis

Thesis level

Doctoral

Date created

2021

Creator

Lindsay Morris

URL

https://figshare.com/articles/thesis/Spatio-temporal_modelling_for_non-stationary_point_reference...

Related subjects

Applied statistics / Spatio-temporal / non-parametric / non-stationary / bayesian / geospatial / covariance / random forest / goodness-of-fit / School: School of Mathematics and Statistics / Applied Statistics / Expanding Knowledge in the Mathematical Sciences / Degree Discipline: Statistics and Operations Research / Degree Level: Doctoral / Degree Name: Doctor of Philosophy

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