Calibration of Scatterplot and Biplot Axes
Package for drawing calibrated scales with tick marks on
(non-orthogonal) variable vectors in scatterplots and biplots.

Package for drawing calibrated scales with tick marks on (non-orthogonal)
variable vectors in scatterplots and biplots. Also provides some functions for multivariate analysis
such principal coordinate analysis.

Package for drawing calibrated scales with tick marks on (non-orthogonal)
variable vectors in scatterplots and biplots. Also provides some functions for biplot creation and
for multivariate analysis such as principal coordinate analysis.

Calibration for Computer Experiments with Binary Responses
Performs the calibration procedure proposed by Sung et al. (2018+) <arXiv:1806.01453>. This calibration method is particularly useful when the outputs of both computer and physical experiments are binary and the estimation for the calibration parameters is of interest.

c(
person(given = "Timo",
family = "Dimitriadis",
role = "aut"),
person(given = "Alexander",
family = "Henzi",
role = "aut"),
person(given = "Marius",
family = "Puke",
role = c("aut", "cre"),
email = "marius.puke@uni-hohenheim.de"))
Package to assess the calibration of probabilistic classifiers using confidence bands for monotonic functions. Besides testing the classical goodness-of-fit null hypothesis of perfect calibration, the confidence bands calculated within that package facilitate inverted goodness-of-fit tests whose rejection allows for a sought-after conclusion of a sufficiently well-calibrated model. The package creates flexible graphical tools to perform these tests.  For construction details see also Dimitriadis, Dümbgen, Henzi, Puke, Ziegel (2022) <arXiv:2203.04065>.
Rcpp, ggplot2, tibble, dplyr, tidyr, sp, methods, base, stats,
magrittr, rlang, tidyselect
Timo Dimitriadis [aut],
Alexander Henzi [aut],
Marius Puke [aut, cre]

Bayesian calibration of complex computer codes
Performs Bayesian calibration of computer models as per
Kennedy and O'Hagan 2001.  The package includes routines to
find the hyperparameters and parameters; see the help page for
stage1() for a worked example using the toy dataset.  A
tutorial is provided in the calex.Rnw vignette; and a suite of
especially simple one dimensional examples appears in
inst/doc/one.dim/.