Description: This is a toolkit for multivariate process monitoring. It computes several multivariate control charts e.g. Hotelling, Chi-squared, MEWMA, MCUSUM and Generalized Variance. Ten didactic datasets are included. It includes some techniques for assessing multivariate normality e.g. Mardia's, Royston's and Henze-Zirkler's tests. Please, see the NEWS file for the latest changes in the package.

Description: This is a toolkit for multivariate process monitoring. It computes several multivariate control charts e.g. Hotelling, Chi-squared, MEWMA, MCUSUM and Generalized Variance. Ten didactic datasets are included. It also contains some tools for assessing multivariate normality e.g. Mardia's, Royston's and Henze-Zirkler's tests. Please, see the NEWS file for the latest changes in the package.

Title: Multi-State Reliability Demonstration Tests (MSRDT)
Description: This is a implementation of design methods for multi-state reliability demonstration tests (MSRDT) with failure count data,
which is associated with the work from the published paper "Multi-state Reliability Demonstration Tests" by Suiyao Chen et al. (2017) <doi:10.1080/08982112.2017.1314493>.
It implements two types of MSRDT, multiple periods (MP) and multiple failure modes (MFM).
For MP, two different scenarios with criteria on cumulative periods (Cum) or separate periods (Sep) are implemented respectively.
It also provides the implementation of conventional design method, namely binomial tests for failure count data.
Imports: gtools, stats, reshape2, dplyr, utils

Title: Tools to Work with Microsoft SQL Server Databases via 'RODBC'
Authors@R: c(person("Arni", "Magnusson", role=c("aut","cre"), email="thisisarni@gmail.com"))
Description: Tools that extend the functionality of the 'RODBC' package to work
with Microsoft SQL Server databases. Makes it easier to browse the database
and examine individual tables and views.

Author: Xiaogang Su, Peter Calhoun, and Juanjuan Fan
Description: Constructs trees for multivariate survival data using marginal and frailty models