Imports: knitr (>= 1.20),magrittr, kableExtra

Title: Dysregulated Pathway Identification Analysis
Authors@R: c(person("Limei", "Wang", role = c("aut", "cre"),
person("Jin", "Li", role = c("aut", "ctb"),
Description: It is used to identify dysregulated pathways based on a pre-ranked gene pair list. A fast algorithm is used to make the computation really fast. The data in package 'DysPIAData' is needed.
Imports: Rcpp (>= 1.0.4), BiocParallel, fastmatch, data.table, stats,

Imports: Rcpp (>= 1.0.4), BiocParallel, fastmatch, data.table,

Title: Background and Pathway Data Used in 'DysPIA'
Description: This dataset includes Background and Pathway data used in package 'DysPIA'.

Title: Management and Processing Tools for Data Produced by the
Authors@R: person("Evan", "Kleiman", email = "evan.kleiman@rutgers.edu",
Description: Process and manage the data from the Empatica E4. All functions operate on the EDA data stream, but other streams will be added soon. The Empatica E4 is a wearable physiological monitor made by Empatica (Empatica is not associated with any of this code). You can find more information about the E4 at Empatica's website <https://www.empatica.com/research/e4/>.
Imports: BBmisc, DataCombine, signal, stats, utils, anytime, chron,
data.table, ggplot2, scales, accelerometry, hms
Packaged: 2019-06-28 12:23:13 UTC; evankleiman

data.table, ggplot2, scales, accelerometry, hms, doParallel,
Packaged: 2019-07-07 13:39:22 UTC; evankleiman

Title: Exponentially Weighted Moving Average with Adjustments to
Authors@R: c(person("Cheng-Kuan Lin", "Developer", role = c("aut", "cre","cph"),
person("Li-Pang Chen", "Su-Fen Yang", role = "aut") )
Description: The univariate statistical quality control tool aims to address measurement error effects when constructing exponentially weighted moving average p control charts. The method primarily focuses on binary random variables, but it can be applied to any continuous random variables by using sign statistic to transform them to discrete ones. With the correction of measurement error effects, we can obtain the corrected control limits of exponentially weighted moving average p control chart and reasonably adjusted exponentially weighted moving average p control charts. The methods in this package can be found in some relevant references, such as Chen and Yang (2022) <arXiv: 2203.03384>; Yang et al. (2011) <doi: 10.1016/j.eswa.2010.11.044>; Yang and Arnold (2014) <doi: 10.1155/2014/238719>; Yang (2016) <doi: 10.1080/03610918.2013.763980> and Yang and Arnold (2016) <doi: 10.1080/00949655.2015.1125901>.
Author: Cheng-Kuan Lin Developer [aut, cre, cph],
Maintainer: Cheng-Kuan Lin Developer <zore2023852@gmail.com>