TY  -  
T1  - Spatiotemporal clustering using Gaussian processes embedded in a mixture model 
SN  -  /  
UR  - http://hdl.handle.net/10138/335461 
T3  -  
A1  - Vanhatalo, Jarno; Foster, Scott D.; Hosack, Geoffrey R. 
A2  -  
PB  -  
Y1  - 2021 
LA  - eng 
AB  - The categorization of multidimensional data into clusters is a common task in statistics. Many applications of clustering, including the majority of tasks in ecology, use data that is inherently spatial and is often also temporal. However, spatiotemporal dependence is typically ignored when clustering multivariate data. We present a finite mixture model for spatial and spatiotemporal clustering that incorporates spatial and spatiotemporal autocorrelation by including appropriate Gaussian process... 
VO  -  
IS  -  
SP  -  
OP  -  
KW  - clustering; community ecology; Gaussian process; Laplace approximation; mixture; regions of common profiles; spatial; spatiotemporal; DEMERSAL FISH; SPATIAL DATA; CLASSIFICATION; INFERENCE; SELECTION; 111 Mathematics 
N1  -   
PP  -  
ER  -