Copyright: See QZ/inst/LAPACK_LICENSE.txt for the files in src/qz/.

Description: Generalized eigenvalues and QZ decomposition
(generalized Schur form) for an N-by-N non-symmetric
matrix A or paired matrices (A,B) with eigenvalues reordering
mechanism. The package is mainly based complex*16 and double
precision of LAPACK library (version 3.4.2.)

Authors@R: c(person("Wei-Chen", "Chen", role = c("aut", "cre"), email=
"wccsnow@gmail.com"), person("LAPACK authors", role = c("aut", "cph")))

Description: Generalized eigenvalues and eigenvectors
use QZ decomposition (generalized Schur decomposition).
The decomposition needs an N-by-N non-symmetric
mechanism. The decomposition functions are mainly based Fortran
subroutines in complex*16 and double precision of LAPACK

Title: Approximation to the Survival Functions of Quadratic Forms of
Description: Calculates the right-tail probability of quadratic forms of Gaussian variables using the skewness-kurtosis ratio matching method, modified Liu-Tang-Zhang method and Satterthwaite-Welch method. The technical details can be found in Hong Zhang, Judong Shen and Zheyang Wu (2020) <arXiv:2005.00905>.

Title: Quantile Autoregressive Distributed Lag Model
Description: Fit the quantile autoregressive distributed lag model proposed by ( Cho et al. (2015) <doi:10.1016/j.jeconom.2015.05.003>).
Imports: stats, dplyr, pbapply, quantreg, MASS

Authors@R: c(person("Gianluca", "Sottile", role=c("aut", "cre"), email = "gianluca.sottile@unipa.it"),
Description: Quantile-based estimators (Q-estimators) can be used to fit any parametric distribution, using its quantile function. Q-estimators are usually more robust than standard maximum likelihood estimators. The method is described in: Sottile G. and Frumento P. (2022). Robust estimation and regression with parametric quantile functions. <doi:10.1016/j.csda.2022.107471>.
Depends: pch, survival, matrixStats, methods, utils
Packaged: 2022-04-01 08:24:47 UTC; gianlucasottile

Title: Quantile-Based Predictors for Survival Outcome
Tingting Zhan [aut, cre, cph] (<https://orcid.org/0000-0001-9971-4844>),
Description: Select optimal quantile-based predictors for
survival outcome, to include the means to handle
dichotomizing the quantiles, mean-signal-intensity or
other continuous markers, and to obtain estimates for
dichotomized predictors by Bootstrap-based bias
Authors@R: c(person(given = 'Misung', family = 'Yi', role =
c('aut', 'cph'), email = 'Misung.Yi@jefferson.edu'),
person(given = 'Tingting', family = 'Zhan', role =
= 'Chervoneva', role = c('aut', 'cph'), email =
Imports: stats, boot, rpart, survival, matrixStats
Collate: '0info.R' 'pkg_data_doc.R' 'optQp.R' 'sampleQp.R'
Packaged: 2022-09-15 15:07:35 UTC; tingtingzhan