Assessing the significance of the correlation between the components of a bivariate Gaussian random field

Assessing the significance of the correlation between the components of a bivariate random field is of great interest in the analysis of spatial data. This problem has been addressed in the literature using suitable hypothesis testing procedures or using coefficients of spatial association between t...

Full description

Autores:

Tipo de recurso:

Fecha de publicación:

2015

Institución:

Universidad Tecnológica de Bolívar

Repositorio:

Repositorio Institucional UTB

Idioma:

eng

OAI Identifier:

oai:repositorio.utb.edu.co:20.500.12585/9009

Acceso en línea:

https://hdl.handle.net/20.500.12585/9009

Palabra clave:

Cross-covariance estimation
Geostatistics
Hypothesis testing
Increasing domain
Power function
Arsenic
Assessment method
Autocorrelation
Estimation method
Geostatistics
Hypothesis testing
Lead
Numerical method
Numerical model
Power law
Spatial data
Testing method
United States
Utah

Rights

restrictedAccess

License

http://creativecommons.org/licenses/by-nc-nd/4.0/