TY - JOUR
T1 - cubble
T2 - an R package for organizing and wrangling multivariate spatio-temporal data
AU - Zhang, H. Sherry
AU - Cook, Dianne
AU - Laa, Ursula
AU - Langrené, Nicolas
AU - Menéndez, Patricia
N1 - Publisher Copyright:
© 2024, American Statistical Association. All rights reserved.
PY - 2024
Y1 - 2024
N2 - Multivariate spatio-temporal data refers to multiple measurements taken across space and time. For many analyses, spatial and time components can be separately studied: for example, to explore the temporal trend of one variable for a single spatial location, or to model the spatial distribution of one variable at a given time. However for some studies, it is important to analyze different aspects of the spatio-temporal data simultaneously, for instance, temporal trends of multiple variables across locations. In order to facilitate the study of different portions or combinations of spatio-temporal data, we introduce a new class, cubble, with a suite of functions enabling easy slicing and dicing on different spatio-temporal components. The proposed cubble class ensures that all the components of the data are easy to access and manipulate while providing flexibility for data analysis. In addition, the cubble package facilitates visual and numerical explorations of the data while easing data wrangling and modelling. The cubble class and the tools implemented in the package are illustrated with examples from climate data analysis.
AB - Multivariate spatio-temporal data refers to multiple measurements taken across space and time. For many analyses, spatial and time components can be separately studied: for example, to explore the temporal trend of one variable for a single spatial location, or to model the spatial distribution of one variable at a given time. However for some studies, it is important to analyze different aspects of the spatio-temporal data simultaneously, for instance, temporal trends of multiple variables across locations. In order to facilitate the study of different portions or combinations of spatio-temporal data, we introduce a new class, cubble, with a suite of functions enabling easy slicing and dicing on different spatio-temporal components. The proposed cubble class ensures that all the components of the data are easy to access and manipulate while providing flexibility for data analysis. In addition, the cubble package facilitates visual and numerical explorations of the data while easing data wrangling and modelling. The cubble class and the tools implemented in the package are illustrated with examples from climate data analysis.
KW - environmental data
KW - exploratory data analysis
KW - R
KW - spatial
KW - spatio-temporal
KW - temporal
UR - http://www.scopus.com/inward/record.url?scp=85203161054&partnerID=8YFLogxK
U2 - 10.18637/jss.v110.i07
DO - 10.18637/jss.v110.i07
M3 - Article
AN - SCOPUS:85203161054
SN - 1548-7660
VL - 110
SP - 1
EP - 27
JO - Journal of Statistical Software
JF - Journal of Statistical Software
IS - 7
ER -