A Fractal Time Series Modeling and Analysis Package

Performs Fractal Analysis and Fractal Regression
c(person(given = "Aaron",
family = "Likens",
role = c("aut", "cre"),
email = "alikens@unomaha.edu",
comment = c(ORCID = "0000-0002-6535-5772")),
person(given = "Travis",
family = "Wiltshire",
role = "aut",
comment = c(ORCID = "0000-0001-7630-2695")))
Various functions for performing fractal and multifractal analysis including performing fractal regression. Please refer to Peng and colleagues (1994) <doi:10.1103/physreve.49.1685>, Kantelhardt and colleagues (2002)<doi:10.1016/S0378-4371(02)01383-3>, and Likens and colleagues (2019) <doi:10.1016/j.physa.2019.121580>.
knitr, markdown, rmarkdown, ggplot2, crqa, MFDFA, fracdiff,
tseries, fields, ifultools, gridExtra, qpdf

Hana Sevcikova <hanas@uw.edu>, Tilmann Gneiting
<tilmann@stat.washington.edu>, Don Percival
<dbp@apl.washington.edu>
Implements various methods for estimating fractal
dimension of time series and 2-dimensional data.

Hana Sevcikova <hanas@uw.edu>,
Don Percival <dbp@apl.washington.edu>,
Tilmann Gneiting <tilmann@stat.washington.edu>
Implements various methods for estimating fractal dimension of time series and 2-dimensional data.

Implements various methods for estimating fractal dimension of time series and 2-dimensional data <doi:10.1214/11-STS370>.

Generate fractal time series with non-normal returns
distribution
The basic principle driving fractal generation of time
series is that data is generated iteratively based on
increasing levels of resolution. The initial series is defined
by a so-called initiator pattern and then generators are used
to replace each segment of the initial pattern. Regular,
repeatable patterns can be produced by using the same seed and
generators. By using a set of generators, non-repeatable time
series can be produced. This technique is the basis of the
fractal time series process in this package.

R (>= 2.8.0), futile.any, futile.logger, timeDate, zoo, xts,
quantmod

futile.any (>= 1.3.0), futile.logger (>= 1.3.0), timeDate,
quantmod
The basic principle driving fractal generation of time
series is that data is generated iteratively based on
increasing levels of resolution.  The initial series is defined
by a so-called initiator pattern and then generators are used
to replace each segment of the initial pattern. Regular,
repeatable patterns can be produced by using the same seed and
generators.  By using a set of generators, non-repeatable time
series can be produced.  This technique is the basis of the
fractal time series process in this package.