Aim is to provide fractional Brownian vector field generation algorithm, Hurst parameter estimation method and fractional kriging model for multivariate data modeling.

Functions for fitting data to a quiescent growth model,
        i.e. a growth process that involves members of the population
        who stop dividing or propagating.

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

Create and visualize fractal trees and fractal forests, based on the Lindenmayer system (L-system). For more details see Lindenmayer (1968a) <doi:10.1016/0022-5193(68)90079-9> and Lindenmayer (1968b) <doi:10.1016/0022-5193(68)90080-5>.

The parameters p and q are estimated with the aid of a randomized Sierpinski Carpet which is built on a [p-p-p-q]-model. Thereby, for three times a simulation with a p-value and once with a q-value is assumed. Hence, these parameters are estimated and displayed. Moreover, functions for simulating random Sierpinski-Carpets with constant and variable probabilities are included. For more details on the method please see Hermann et al. (2015) <doi:10.1002/sim.6497>.

Estimate the of fractal dimension of a black area in 2D and 3D (slices) images using the box-counting method. See Klinkenberg B. (1994) <doi:10.1007/BF02065874>.

Turn numeric,data.frame,matrix into fraction form.

The main function of this package allows numerical vector objects to
  be displayed with their values in vulgar fractional form.  This is convenient if
  patterns can then be more easily detected.  In some cases replacing the components
  of a numeric vector by a rational approximation can also be expected to remove
  some component of round-off error.  The main functions form a re-implementation
  of the functions 'fractions' and 'rational' of the MASS package, but using a
  radically improved programming strategy.

Provides functions for converting decimals to a matrix of
    numerators and denominators or a character vector of fractions.
    Supports mixed or improper fractions, finding common denominators for
    vectors of fractions, limiting denominators to powers of ten, and
    limiting denominators to a maximum value.  Also includes helper
    functions for finding the least common multiple and greatest common
    divisor for a vector of integers.  Implemented using C++ for maximum
    speed.