Bickel, D.R., Rahal, A. (2019) <https://tinyurl.com/kkdc9rk8>.

Title: A collection of functions for graphing correlation matrices
Description: Correlplot contains diverse routines for the construction of different plots for representing correlation matrices.

Title: A Collection of Functions for Graphing Correlation Matrices
Description: Routines for the graphical representation of correlation matrices by means of correlograms, biplots and MDS maps.

Author: Luciano Souza <lcnsza@gmail.com>, Lucas Gallindo <lgallindo@gmail.com>, Luciano Serafim de Souza <lucianoserafimdesouza@gmail.com>
Description: Density, distribution function, quantile function, random
generation and survival function for the Cosine Weibull Distribution as defined
by SOUZA, L. New Trigonometric Class of Probabilistic Distributions. 219 p.
Thesis (Doctorate in Biometry and Applied Statistics) - Department of Statistics
and Information, Federal Rural University of Pernambuco, Recife, Pernambuco,
2015 (available at <http://www.openthesis.org/documents/New-trigonometric-classes-probabilistic-distributions-602633.html>) and BRITO, C. C. R. Method Distributions generator and
Probability Distributions Classes. 241 p. Thesis (Doctorate in Biometry and
Applied Statistics) - Department of Statistics and Information, Federal Rural
University of Pernambuco, Recife, Pernambuco, 2014 (available upon request).

Title: Photometric redshift estimation using generalized linear models
Author: Rafael S. de Souza, Alberto Krone-Martins, Jonathan Elliott, Joseph
Maintainer: Rafael S. de Souza <rafael.2706@gmail.com>
Description: User-friendly interfaces to perform fast and reliable photometric
redshift estimation. The code makes use of generalized linear models and
can adopt gamma or inverse gaussian families, either from a frequentist or
a Bayesian perspective. The code additionally provides a Shiny application
Imports: ggplot2, ggthemes, arm, COUNT, gridExtra, pcaPP, mvtnorm,

Title: Estimation and Inference Methods for Counterfactual Analysis
Author: Mingli Chen, Victor Chernozhukov, Ivan Fernandez-Val, Blaise Melly
Description: Implements the estimation and inference methods for counterfactual analysis described in Chernozhukov, Fernandez-Val and Melly (2013) <DOI:10.3982/ECTA10582> "Inference on Counterfactual Distributions," Econometrica, 81(6). The counterfactual distributions considered are the result of changing either the marginal distribution of covariates related to the outcome variable of interest, or the conditional distribution of the outcome given the covariates. They can be applied to estimate quantile treatment effects and wage decompositions.
Imports: survival, Hmisc, foreach, doRNG, doParallel, parallel