Packaged: 2022-09-28 15:11:58 UTC; Jose M Pavia

Author: Jichun Xie <jichun@mail.med.upenn.edu>, Justine Shults <jshults@mail.med.upenn.edu>
Description: QLS is a two-stage computational approach for estimation of the correlation parameters within the framework of GEE. It helps solving parameters in mean, scale, and correlation structures for longitudinal data.
Packaged: Fri Jun 20 23:32:36 2008; jxie

Author: Jichun Xie <jichun@mail.med.upenn.edu>, Justine Shults
Description: QLS is a two-stage computational approach for estimation
of the correlation parameters within the framework of GEE. It
helps solving parameters in mean, scale, and correlation

Title: Quantile-mapping for post-processing climate model output
Description: Empirical adjustment of the distribution of variables
originating from (regional) climate model simulations using

Title: Statistical transformations for post-processing climate model

Description: Empirical adjustment of the distribution of variables originating from (regional) climate model simulations using quantile mapping.

Title: Statistical Transformations for Post-Processing Climate Model

Title: Quantification of Multivariate Dependence
Description: A multivariate copula-based dependence measure. For more information, see Griessenberger, Junker, Trutschnig (2021), On a multivariate copula-based dependence measure and its estimation, <arXiv:2109.12883>.

Description: A multivariate copula-based dependence measure. For more information, see Griessenberger, Junker, Trutschnig (2022), On a multivariate copula-based dependence measure and its estimation, Electronic Journal of Statistics, 16, 2206-2251.
Imports: qad, Rcpp (>= 1.0.6), ggplot2, cowplot, dplyr, utils

Title: Analysis of subjective perspectives using Q methodology
Authors@R: c(person(given="Aiora", family="Zabala", email="aiora.zabala@gmail.com", role=c("aut", "cre")))
Description: Performs a full analysis of Q methodology data. Type \code{help(package=qmethod)} for a full overview.

Description: Analyses Q methodology data to identify the distinct perspectives existing within a group. This methodology is used across social, health and environmental sciences to understand diversity of attitudes, discourses, or decision-making styles. The function qmethod() runs the full analysis and each step can be run separately using the corresponding functions: qflag() for automatic flagging of Q-sorts (manual flagging is optional), qzscores() for scores for statements, qda() for distinguishing and consensus statements, and qfcharact() for general characteristics of the factors. It includes a function to import data from PQMethod software, to export plain text data for interpretation in two flavours, and to plot Q method results. The package uses principal components and it offers the following choices: manual or automatic flagging, a number of mathematical methods for rotation, and a number of correlation coefficients for the initial correlation matrix.