The qrfactor package simultaneously runs both Q and R  mode factor analyses. The package contains only one function called qrfactor() that can perform PCA, R-mode Factor Analysis, Q-mode Factor Analysis, Simultaneous R- and Q-mode Factor Analysis, Principal Coordinate Analysis, as wells as Multidimensional Scaling  (MDS). Loadings and scores can easily be computed from the  simulation.The plot.qrfactor() function offers several annotated  biplots for all possible combinations of eigenvectors, loadings, and scores. Input data includes shapefiles, tables and dataframe

Quantile Regression Model for Residual Lifetime Using an Induced
Smoothing Approach
c(person("Kyu Hyun", "Kim", email = "kyuhyunkim07@yonsei.ac.kr", role = c("aut", "cre")),
person("Sangwook", "Kang", role = "aut"),
person("Sy Han", "Chiou", role = "aut"))
A collection of functions to fit quantiles regression models for censored residual lifetimes. It provides various options for regression parameters estimation: the induced smoothing approach (smooth), and L1-minimization (non-smooth).  It also implements the estimation methods for standard errors of the regression parameters estimates based on an efficient partial multiplier bootstrap method and robust sandwich estimator. Furthermore, a simultaneous procedure of estimating regression parameters and their standard errors via an iterative updating procedure is implemented (iterative). See Kim, K. (2022) "Smoothed quantile regression for censored residual life", <arXiv:2205.00413>.
nleqslv, quantreg, stringr, survival, ggplot2, Rcpp
Kyu Hyun Kim [aut, cre],
Sangwook Kang [aut],
Sy Han Chiou [aut]

Joint Estimation in Linear Quantile Regression
R (>= 2.6), stats, graphics, grDevices, quantreg
Joint estimation of quantile specific intercept and slope parameters in a linear regression setting.

Surya Tokdar <surya.tokdar@duke.edu> and Erika Cunningham <erika.ball@duke.edu>

splines, coda, Matrix, kernlab, quantreg

Data Sets for Quantitative Risk Management Practice
Various data sets (stocks, stock indices, constituent data, FX,
zero-coupon bond yield curves, volatility, commodities) for Quantitative
Risk Management practice.
c(person(given = "Marius", family = "Hofert", role = c("aut", "cre"),
email = "marius.hofert@uwaterloo.ca"),
person(given = "Kurt", family = "Hornik", role = "aut",
email = "Kurt.Hornik@R-project.org"))
Marius Hofert [aut, cre], Kurt Hornik [aut]