Maximal Fat Oxidation and Kinetics Calculation
c(person("Jorge R",
"Fernandez-Santos",
role = c("aut", "cre"),
email = "jorgedelrosario.fernandez@uca.es",
comment = c(ORCID = "https://orcid.org/0000-0002-5047-2976")),
person("Jesus G",
"Ponce-Gonzalez",
role = "ctb",
comment = c(ORCID = "https://orcid.org/0000-0002-5982-7761")),
person("Cristina",
"Casals",
role = "ctb",
comment = c(ORCID = "https://orcid.org/0000-0002-6992-0492")),
person("Jose L",
"Gonzalez-Montesinos",
role = "ctb",
comment = c(ORCID = "https://orcid.org/0000-0002-6867-7718")),
person("Juan",
"Corral-Perez",
role = "ctb",
comment = c(ORCID = "https://orcid.org/0000-0002-6574-9827")),
person("Alejandro",
"Perez-Bey",
role = "ctb",
comment = c(ORCID = "https://orcid.org/0000-0002-9849-5544")))
Calculate the maximal fat oxidation, the exercise intensity that elicits the
maximal fat oxidation and the SIN model to represent the fat oxidation kinetics.
Three variables can be obtained from the SIN model: dilatation, symmetry and translation.
Examples of these methods can be found in Montes de Oca et al (2021) <doi:10.1080/17461391.2020.1788650>
and Chenevière et al. (2009) <doi:10.1249/MSS.0b013e31819e2f91>.
stats, dplyr, ggplot2, magrittr, tibble, minpack.lm, openxlsx,
readxl, stringr, tidyr
Jorge R Fernandez-Santos [aut, cre]
(<https://orcid.org/0000-0002-5047-2976>),
Jesus G Ponce-Gonzalez [ctb] (<https://orcid.org/0000-0002-5982-7761>),
Cristina Casals [ctb] (<https://orcid.org/0000-0002-6992-0492>),
Jose L Gonzalez-Montesinos [ctb]
(<https://orcid.org/0000-0002-6867-7718>),
Juan Corral-Perez [ctb] (<https://orcid.org/0000-0002-6574-9827>),
Alejandro Perez-Bey [ctb] (<https://orcid.org/0000-0002-9849-5544>)

Multivariate Functional Principal Component Analysis for Data
Observed on Different Dimensional Domains
person("Clara", "Happ", email = "clara.happ@stat.uni-muenchen.de",
role = c("aut", "cre"))
Calculate a multivariate functional principal component analysis
for data observed on different dimensional domains. The estimation algorithm
relies on univariate basis expansions for each element of the multivariate
functional data. Multivariate and univariate functional data objects are
represented by S4 classes for this type of data implemented in the package
'funData'.
abind, foreach, irlba, Matrix, methods, mgcv, plyr, stats