Package: catseyes
Type: Package
Title: Create Catseye Plots Illustrating the Normal Distribution of the
Means
Version: 0.2.5
Authors@R: person("Clark", "Andersen", email = "crandersen@mdanderson.org", role=c("cre","aut"))
Description: Provides the tools to produce catseye plots, principally
by catseyesplot() function which calls R's standard plot() function internally, or alternatively
by the catseyes() function to overlay the catseye plot onto an existing
R plot window. Catseye plots illustrate the normal distribution of the mean (picture a
normal bell curve reflected over its base and rotated 90 degrees), with a shaded confidence
interval; they are an intuitive way of illustrating and comparing normally distributed estimates,
and are arguably a superior alternative to standard confidence intervals, since they show the full
distribution rather than fixed quantile bounds. The catseyesplot and catseyes functions require
pre-calculated means and standard errors (or standard deviations), provided as numeric vectors;
this allows the flexibility of obtaining this information from a variety of sources, such as
direct calculation or prediction from a model.  Catseye plots, as illustrations of the
normal distribution of the means, are described in Cumming (2013 & 2014).
Cumming, G. (2013). The new statistics: Why and how. Psychological Science, 27, 7-29. <doi:10.1177/0956797613504966> pmid:24220629.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Suggests: emmeans
NeedsCompilation: no
Packaged: 2020-05-07 19:37:09 UTC; CRAndersen
Author: Clark Andersen [cre, aut]
Maintainer: Clark Andersen <crandersen@mdanderson.org>
Repository: CRAN
Date/Publication: 2020-05-08 16:40:02 UTC

Title: Binary and Categorical Image Similarity Index
Description: Computes a structural similarity metric (after the style of
MS-SSIM for images) for binary and categorical 2D and 3D images. Can be
based on accuracy (simple matching), Cohen's kappa, Rand index, adjusted
Rand index, Jaccard index, Dice index, normalized mutual information, or
adjusted mutual information. In addition, has fast computation
of Cohen's kappa, the Rand indices, and the two mutual informations.
Implements the methods of Thompson and Maitra (2020) <arXiv:2004.09073>.
Author: Geoffrey Thompson [aut, cre] (<https://orcid.org/0000-0003-2436-8822>)