Contains Lioness Algorithm (LA) for finding optimal designs over continuous design space, optimal Latin hypercube designs, and optimal order-of-addition designs. LA is a brand new nature-inspired meta-heuristic optimization algorithm. Detailed methodologies of LA and its implementation on numerical simulations can be found at Hongzhi Wang, Qian Xiao and Abhyuday Mandal (2021) <arXiv:2010.09154>.

c(
person("Hongzhi", "Wang", email="wanghongzhi.ut@gmail.com", role=c("aut","cre")),
person("Qian", "Xiao", role="aut"),
person("Abhyuday", "Mandal", role="aut"))

Interface to the Lake Multi-Scaled Geospatial and Temporal
Database
c(
person("Joseph", "Stachelek",
email = "stachel2@msu.edu",
role = c("aut", "cre"),
comment = c(ORCID = c("0000-0002-5924-2464"))),
person("Samantha","Oliver",
role = c("aut"),
comment = c(ORCID = c("0000-0001-5668-1165"))),
person("Farzan","Masrour", role = c("aut"))
)
Client for programmatic access to the Lake
Multi-scaled Geospatial and Temporal database <https://lagoslakes.org>, with functions
for accessing lake water quality and ecological context data for the US.
testthat, knitr, rmarkdown, devtools, prettydoc, R.rsp
Joseph Stachelek [aut, cre] (0000-0002-5924-2464),
Samantha Oliver [aut] (0000-0001-5668-1165),
Farzan Masrour [aut]

dplyr (>= 0.7.0), rappdirs (>= 0.3.1), lazyeval (>= 0.2),
purrr (>= 0.2.2.2), magrittr (>= 1.5), sf, curl (>= 2.7.0),
stringr (>= 1.2.0), tibble, tidyr, memoise, rlang, progress
testthat, knitr, rmarkdown, devtools, R.rsp, printr, ggplot2
Joseph Stachelek [aut, cre] (<https://orcid.org/0000-0002-5924-2464>),
Samantha Oliver [aut] (<https://orcid.org/0000-0001-5668-1165>),
Farzan Masrour [aut]

dplyr (>= 0.7.0), rappdirs (>= 0.3.1), lazyeval (>= 0.2),
purrr (>= 0.2.2.2), magrittr (>= 1.5), sf, curl (>= 2.7.0),
stringr (>= 1.2.0), tibble, tidyr, memoise, rlang, progress, qs

Contains some procedures for latent variable modelling with a
particular focus on multilevel data.
The LAM package contains mean and covariance structure modelling
for multivariate normally distributed data ('mlnormal'),
a general Metropolis-Hastings algorithm ('amh') and penalized
maximum likelihood estimation ('pmle').
CDM, coda, graphics, Rcpp, sirt (>= 2.0), stats, utils