testthat (>= 2.1.0), RColorBrewer, plot3D, pracma, spTimer,
maps

Regularized Principal Component Analysis for Spatial Data
This package provides regularized principal component
analysis incorporating smoothness, sparseness and orthogonality of
eigenfunctions by using alternating direction method of multipliers (ADMM)
algorithm.

Provide regularized principal component analysis incorporating smoothness, sparseness and orthogonality of eigenfunctions by using the alternating direction method of multipliers algorithm. The method can be applied to either regularly or irregularly spaced data.

Provide regularized principal component analysis incorporating smoothness,
sparseness and orthogonality of eigenfunctions by using the alternating direction method of
multipliers algorithm. The method can be applied to either regularly or irregularly spaced
data (Wang and Huang, 2017).

Provide regularized principal component analysis incorporating smoothness,
sparseness and orthogonality of eigenfunctions by using the alternating direction method of
multipliers algorithm (Wang and Huang, 2017, <DOI:10.1080/10618600.2016.1157483>). The method can be applied to either regularly or irregularly spaced
data, including 1D, 2D, and 3D.

Provide regularized principal component analysis incorporating smoothness, sparseness and orthogonality of eigenfunctions
by using the alternating direction method of multipliers algorithm (Wang and Huang, 2017, <DOI:10.1080/10618600.2016.1157483>). The
method can be applied to either regularly or irregularly spaced data, including 1D, 2D, and 3D.

c(person(
given = "Wen-Ting",
family = "Wang",
email = "egpivo@gmail.com",
role = c("aut", "cre"),
comment = c(ORCID = "0000-0003-3051-7302")
),
person(
given = "Hsin-Cheng",
family = "Huang",
email = "hchuang@stat.sinica.edu.tw",
role = "aut",
comment = c(ORCID = "0000-0002-5613-349X")
)
)
knitr, rmarkdown, testthat (>= 2.1.0), dplyr (>= 1.0.3),
gifski, tidyr, fields, scico, plot3D, pracma, RColorBrewer,
maps, covr

person("Stamatis", "Kalogirou", email = "stamatis@lctools.science",
role = c("aut", "cre"))
Provides a set of spatial accessibility measures from a set of locations
(demand) to another set of locations (supply). It aims, among others,
to support research on spatial accessibility to health care facilities.
Includes the locations and some characteristics of major public hospitals in Greece.