Title: Package for Brik, Fabrik and Fdebrik Algorithms to Initialise
Alice Parodi, Mirco Patriarca, Laura Sangalli, Piercesare Secchi,
Simone Vantini and Valeria Vitelli, as contributors.
Depends: R (>= 3.1.0), boot, cluster, depthTools, splines, splines2,
Description: Implementation of the BRIk, FABRIk and FDEBRIk algorithms
to initialise k-means. These methods are intended for the
It makes use of the functions kma and kma.similarity, from the
archived package fdakma, by Alice Parodi et al.

Generate digital LEGO models using 'tidyverse' functions.
Convert image files into 2D and 3D LEGO mosaics, complete with piece counts and instructions.
Render 3D models using simple data frame instructions.
Developed under the LEGO Group's Fair Play policy <https://www.lego.com/en-us/legal/notices-and-policies/fair-play/>.
Imports: ggplot2, magrittr, dplyr, tidyr, purrr, scales, farver,
Suggests: knitr, rmarkdown, gridExtra, png, jpeg, tibble, raster,

Title: Brier score decomposition of probabilistic forecasts for binary
Description: Description of bride package

Description: Decomposes the empirical Brier score into reliability,
resolution and uncertainty. Two different estimators for the
components are provided: The original estimators proposed by
Murphy (1974), and the bias-corrected estimators proposed by
Ferro and Fricker (2012). Variances of all the components are
estimated. This package applies only to probabilistic

Description: Decomposes the empirical Brier score into reliability, resolution and uncertainty. Two different estimators for the components are provided: The original estimators proposed by Murphy (1974), and the bias-corrected estimators proposed by Ferro and Fricker (2012). Sampling variances of all the components are estimated. This package applies only to probabilistic predictions of binary events.

Title: An Implementation of the Bridge Distribution with Logit-Link as
Authors@R: person("Bruce", "Swihart", email = "bruce.swihart@gmail.com", role = c("aut", "cre"))
Description: An implementation of the bridge distribution with logit-link in
R. In Wang and Louis (2003) <DOI:10.1093/biomet/90.4.765>, such a univariate
bridge distribution was derived as the distribution of the random intercept that
'bridged' a marginal logistic regression and a conditional logistic regression.
The conditional and marginal regression coefficients are a scalar multiple
of each other. Such is not the case if the random intercept distribution was
Suggests: knitr, rmarkdown, reshape2, ggplot2, testthat
Packaged: 2016-04-22 13:17:23 UTC; swihartbj