c(
person(given = "Lennart",
family = "Oelschl\U00E4ger",
role = c("aut", "cre"),
email = "oelschlaeger.lennart@gmail.com",
comment = c(ORCID = "0000-0001-5421-9313")),
person(given = "Timo",
family = "Adam",
role = "aut",
email = "ta59@st-andrews.ac.uk"),
person(given = "Rouven",
family = "Michels",
role = "aut",
email = "r.michels@uni-bielefeld.de"))
Lennart Oelschläger [aut, cre]
(<https://orcid.org/0000-0001-5421-9313>),
Timo Adam [aut],
Rouven Michels [aut]

parallel, doSNOW, rmarkdown, knitr, testthat (>= 3.0.0),
covr, printr, tseries, spelling

c(
person(given = "Lennart",
family = "Oelschl\U00E4ger",
role = c("aut", "cre"),
email = "oelschlaeger.lennart@gmail.com",
comment = c(ORCID = "0000-0001-5421-9313")),
person(given = "Timo",
family = "Adam",
role = "aut",
email = "ta59@st-andrews.ac.uk",
comment = c(ORCID = "0000-0001-9079-3259")),
person(given = "Rouven",
family = "Michels",
role = "aut",
email = "r.michels@uni-bielefeld.de",
comment = c(ORCID = "0000-0002-5433-6197")))
Fitting (hierarchical) hidden Markov models to financial data
via maximum likelihood estimation. See Oelschläger, L. and Adam, T.
"Detecting bearish and bullish markets in financial time series using
hierarchical hidden Markov models" (2021, Statistical Modelling)
<doi:10.1177/1471082X211034048> for a reference.

Classic, reloaded and adaptive FastICA algorithms
The package includes classic symmetric and deflation-based FastICA algorithms, reloaded deflation-based FastICA and an algorithm for adaptive deflation-based FastICA using multiple contrast functions.

Classical, Reloaded and Adaptive FastICA Algorithms
Algorithms for classical symmetric and deflation-based FastICA, reloaded deflation-based FastICA algorithm and an algorithm for adaptive deflation-based FastICA using multiple nonlinearities.

Algorithms for classical symmetric and deflation-based FastICA, reloaded deflation-based FastICA algorithm and an algorithm for adaptive deflation-based FastICA using multiple nonlinearities. For details, see Miettinen et al. (2014) <doi:10.1109/TSP.2014.2356442> and Miettinen et al. (2017) <doi:10.1016/j.sigpro.2016.08.028>.