c(person(given = "Jakub",
family = "Stoklosa",
role = c("aut", "cre"),
email = "j.stoklosa@unsw.edu.au",
comment = c(ORCID = "0000-0002-6523-4524")),
person(given = "Wenhan",
family = "Hwang",
role = c("aut", "ctb")),
person(given = "David",
family = "Warton",
role = c("aut", "ctb")),
person(given = "Jeremy",
family = "Vanderwal",
role = "ctb",
email = "jjvanderwal@@gmail.com",
comment = c("Used the wt.var() function written by Jeremy VanDerWal")))
Fits measurement error models using Monte Carlo Expectation Maximization (MCEM). For specific details on the methodology, see: Greg C. G. Wei & Martin A. Tanner (1990) A Monte Carlo Implementation of the EM Algorithm and the Poor Man's Data Augmentation Algorithms, Journal of the American Statistical Association, 85:411, 699-704 <doi:10.1080/01621459.1990.10474930> For more examples on measurement error modelling using MCEM, see the 'RMarkdown' vignette: "'refitME' R-package tutorial".
MASS, SemiPar, mgcv, VGAM, VGAMdata, caret, expm, mvtnorm,
sandwich, stats, dplyr
Jakub Stoklosa [aut, cre] (<https://orcid.org/0000-0002-6523-4524>),
Wenhan Hwang [aut, ctb],
David Warton [aut, ctb],
Jeremy Vanderwal [ctb] (Used the wt.var() function written by Jeremy
VanDerWal)

c(person(given = "Jakub",
family = "Stoklosa",
role = c("aut", "cre"),
email = "j.stoklosa@unsw.edu.au",
comment = c(ORCID = "0000-0002-6523-4524")),
person(given = "Wenhan",
family = "Hwang",
role = c("aut", "ctb")),
person(given = "David",
family = "Warton",
role = c("aut", "ctb")))
MASS, SemiPar, mgcv, VGAM, VGAMdata, caret, expm, mvtnorm,
sandwich, stats, dplyr, scales
Jakub Stoklosa [aut, cre] (<https://orcid.org/0000-0002-6523-4524>),
Wenhan Hwang [aut, ctb],
David Warton [aut, ctb]

Refining Data Table Using a Set of Formulas
A tool for refining data frame with formulas.

c(
person("Óscar", "Lado-Baleato",email="oscarlado.baleato@usc.es", role =c("cre","aut")),
person("Javier", "Roca-Pardiñas", email="roca@uvigo.es", role =c("aut", "ctb")),
person("Carmen", "Cadarso-Suárez",email="carmen.cadarso@usc.es", role = c("aut", "ths")),
person("Gude","Francisco",email="francisco.gude.sampedro@sergas.es", role = c("aut", "ths"))
)
An R package for estimating conditional multivariate reference regions.
The reference region is non parametrically estimated using a kernel density estimator.
Covariates effects on the multivariate response means vector and variance-covariance
matrix, thus on the region shape, are estimated by flexible additive predictors.
Continuous covariates non linear effects might be estimated using penalized splines smoothers.
Confidence intervals for the covariates estimated effects might be derived from
bootstrap resampling. Kernel density bandwidth can be estimated with different methods, including
a method that optimize the region coverage. Numerical, and graphical, summaries
can be obtained by the user in order to evaluate reference region performance with real data.
Full mathematical details can be found in <doi:10.1007/s00477-020-01901-1>.
Óscar Lado-Baleato [cre, aut],
Javier Roca-Pardiñas [aut, ctb],
Carmen Cadarso-Suárez [aut, ths],
Gude Francisco [aut, ths]