qAnalyst performs: control charts for variables and attributes according to Douglas C. Montgomery Introduction to Statistical Quality Control book, Capability analysis for normal and non - normal distributions and Distributions Identification

qAnalyst performs: control charts for variables and
attributes according to Douglas C. Montgomery Introduction to
Statistical Quality Control book, Capability analysis for
normal and non - normal distributions and Distributions
Identification

Control Charts, Capability and Distribution Identification

Quantitative Classification by Association Rules
CBA postprocessing algorithm that creates smaller models for datasets containing quantitative (numerical) attributes. Article describing QCBA is published in Tomas Kliegr (2017) <arXiv:1711.10166>.

arulesCBA (>= 1.1.2), rCBA (>= 0.3.0), sbrl, stringr

CBA postprocessing algorithm that creates smaller models for datasets containing quantitative (numerical) attributes. Article describing QCBA is published in Tomas Kliegr (2017) <arXiv:1711.10166>. The package can also postprocess results of the SBRL package, which is no longer in CRAN, but can be obtained from <https://github.com/cran/sbrl>.
arulesCBA (>= 1.2.0), rCBA (>= 0.3.0), stringr

Emerson Luis de Santa Helena <elsh@ufs.br>
Wagner Santos de Lima <wagnersantos.ufs@hotmail.com>
Wagner Santos de Lima <wagnersantos.ufs@hotmail.com>
Density, distribution function, quantile function and
random generation for the q-gaussian distribution with parameters mu and sig.

Rcpp (>= 0.12.10) , robustbase , zipfR , stats

Rcpp (>= 0.12.10), stats, robustbase, zipfR

Jingyi Xin, Bibhas Chakraborty, and Eric B. Laber
Functions to implement Q-learning for estimating optimal
dynamic treatment regimes from two stage sequentially
randomized trials, and to perform inference via m-out-of-n
bootstrap for parameters indexing the optimal regime.

Methods for Quantitative Magnetic Resonance Imaging ('qMRI')
c(person("Joerg", "Polzehl", role = c("aut"),
email = "joerg.polzehl@wias-berlin.de"),
person("Karsten", "Tabelow", role = c("aut", "cre"),
email = "karsten.tabelow@wias-berlin.de"),
person("WIAS Berlin", role = c("cph", "fnd")))
Implementation of methods for estimation of quantitative maps
from Multi-Parameter Mapping (MPM) acquisitions (Weiskopf et al. (2013)
<doi:10.3389/fnins.2013.00095>) including adaptive
smoothing methods in the framework of the ESTATICS model
(Estimating the apparent transverse relaxation time (R2*) from images with
different contrasts, Weiskopf et al. (2014) <doi:10.3389/fnins.2014.00278>).
The smoothing method is described in Mohammadi et al. (2017).
<doi:10.20347/WIAS.PREPRINT.2432>.
This package is Copyright (C) 2015-2019 Weierstrass
Institute for Applied Analysis and Stochastics.
Joerg Polzehl [aut],
Karsten Tabelow [aut, cre],
WIAS Berlin [cph, fnd]