Statistical methods for anthropometric data oriented towards the
ergonomic design of products
Guillermo Vinue, Irene Epifanio, Amelia Simo, M. Victoria Ibanez, Juan Domingo, Guillermo Ayala
This package brings together some statistical methodologies especially developed to analyze anthropometric data. These methods are aimed 		at providing effective solutions to some commons problems related to Ergonomics and Anthropometry. They are based on clustering, the 		statistical concept of data depth, the statistical shape analysis and the archetypal analysis.
shapes, rgl, archetypes, nnls, depth, FNN, ICGE, cluster
knitr, biclust, calibrate, mvtnorm, SportsAnalytics,
RColorBrewer, plotrix, abind

Statistical Methods for Anthropometric Data
Anthropometry brings together some statistical methodologies especially developed to analyze anthropometric data. These methods are aimed 		at providing effective solutions to some commons problems related to Ergonomics and Anthropometry. They are based on clustering, the 		statistical concept of data depth, statistical shape analysis and archetypal analysis.
shapes, rgl, archetypes, nnls, depth, FNN, ICGE, cluster,
biclust
knitr, calibrate, mvtnorm, SportsAnalytics, RColorBrewer,
plotrix, abind

Statistical methodologies especially developed to analyze anthropometric data. These methods are aimed 		at providing effective solutions to some commons problems related to Ergonomics and Anthropometry. They are based on clustering, the 		statistical concept of data depth, statistical shape analysis and archetypal analysis.

Statistical methodologies especially developed to analyze anthropometric data. These methods are aimed 		at providing effective solutions to some commons problems related to Ergonomics and Anthropometry. They are based on clustering, the 		statistical concept of data depth, statistical shape analysis and archetypal analysis. Please see Vinue (2017) <doi:10.18637/jss.v077.i06>.

Antibody Titer Analysis of Vaccinated Patients
c(person("Yuuki", "Mizumoto", role=c("aut")),
person("Hiroaki", "Kato", role=c("aut", "cre"),
email="hkato@med.shimane-u.ac.jp", comment=c(ORCID="0000-0001-9591-1875")),
person("Takeshi", "Urano", role=c("ctb")))
Yuuki Mizumoto [aut],
Hiroaki Kato [aut, cre] (<https://orcid.org/0000-0001-9591-1875>),
Takeshi Urano [ctb]
Visualization of antibody titer scores is valuable for examination of vaccination
effects. 'AntibodyTiters' visualizes antibody titers of all or selected patients. This
package also produces empty excel files in a specified format, in which users can fill in
experimental data for visualization. Excel files with toy data can also be produced, so that
users can see how it is visualized before obtaining real data. The data should contain
titer scores at pre-vaccination, after-1st shot, after-2nd shot, and at least one
additional sampling points. Patients with missing values can be included. The first two
sampling points (pre-vaccination and after-1st shot) will be plotted discretely, whereas
those following will be plotted on a continuous time scale that starts from the day of
second shot. Half-life of titer can also be calculated for each pair of sampling points.