mvtnorm (>= 1.0), multcompView, gmp, Rmpfr, SuppDists,
kSamples (>= 1.2.7), BWStest (>= 0.2.1), MASS, stats

Penalized Multi-Band Learning for Circadian Rhythm Analysis
Using Actigraphy
c(person(given = "Xinyue",
family = "Li",
email = "xinyue.li@yale.edu",
role = c("aut", "cre")),
person(given="Michael",
family="Kane",
email = "michael.kane@yale.edu",
role = c("aut")))
Penalized Multi-Band Learning algorithm can be effectively implemented for circadian rhythm analysis and daily activity pattern characterization using actigraphy (continuously measured objective physical activity data). Functions for interactive visualization of actigraph data are also included. Method reference: Li, X., Kane, M., Zhang, Y., Sun, W., Song, Y., Dong, S., Lin, Q., Zhu, Q., Jiang, F., Zhao, H. (2019) A Novel Penalized Multi-band Learning Approach Characterizes the Consolidation of Sleep-Wake Circadian Rhythms During Early Childhood Development.
Xinyue Li [aut, cre],
Michael Kane [aut]

Manuel Russon <manuekrusson@gmail.com>, Xuanhua "Peter" Yin <peteryin.sju@hotmail.com>
Miscellaneous functions for data analysis, graphics, data manipulation, statistical investigation, including descriptive statistics, creating leading and lagging variables, portfolio return analysis, time series difference and percentage change calculation, stacking data for higher efficient analysis.

Manuel Russon <manuelrusson@gmail.com>, Xuanhua "Peter" Yin <peteryin.sju@hotmail.com>

person(given = "Enrico", family = "Schumann",
role  = c("aut", "cre"),
email = "es@enricoschumann.net",
comment = c(ORCID = "0000-0001-7601-6576"))
Functions and examples for 'Portfolio
Management with R': backtesting investment and
trading strategies, computing profit/loss and
returns, analysing trades, handling lists of
transactions, reporting, and more.
NMOF, crayon, datetimeutils, fastmatch, orgutils, parallel,
textutils, utils, zoo

NMOF, datetimeutils, fastmatch, orgutils, parallel, textutils,
utils, zoo

http://enricoschumann.net/PMwR/ ,
https://git.sr.ht/~enricoschumann/PMwR ,
https://gitlab.com/enricoschumann/PMwR ,
https://github.com/enricoschumann/PMwR