2D Boxcount for 1D signal

fd_boxcount2D(
y = NA,
unitSquare = TRUE,
image2D = NA,
resolution = 1,
removeTrend = FALSE,
polyOrder = 1,
scaleMin = 0,
scaleMax = floor(log2(NROW(y) * resolution)),
scaleS = NA,
dataMin = 2^(scaleMin + 1),
maxData = 2^(scaleMax - 1),
doPlot = FALSE,
returnPlot = FALSE,
returnPLAW = FALSE,
returnInfo = FALSE,
returnLocalScaling = FALSE,
silent = FALSE,
noTitle = FALSE,
tsName = "y"
)

## Arguments

y

A numeric vector or time series object.

unitSquare

Create unit square image of y? This is required for estimating FD of time series (default = TRUE)

image2D

A matrix representing a 2D image, argument y and unitSquare will be ignored (default = NA)

resolution

The resolution used to embed the timeseries in 2D, a factor by which the dimensions the matrix will be multiplied (default = 1)

removeTrend

If TRUE, will call ts_detrend on y (default = FALSE)

polyOrder

Order of polynomial trend to remove if removeTrend = TRUE

standardise

Standardise y using ts_standardise() with adjustN = FALSE (default = none)

Adjust the order of the time series (by summation or differencing), based on the global scaling exponent, see e.g. https://www.frontiersin.org/files/Articles/23948/fphys-03-00141-r2/image_m/fphys-03-00141-t001.jpgIhlen (2012) (default = FALSE)

scaleMin

Minimium scale value (as 2^scale) to use (default = 0)

scaleMax

Maximum scale value (as 2^scale) to use (default = max of log2(nrows) and log2(ncols))

scaleS

If not NA, pass a numeric vector listing the scales (as a power of 2) on which to evaluate the boxcount. Arguments scaleMax, scaleMin, and scaleResolution will be ignored (default = NA)

dataMin

Minimum number of time/data points inside a box for it to be included in the slope estimation (default = 2^scaleMin)

maxData

Maximum number of time/data points inside a box for it to be included in the slope estimation (default = 2^scaleMax)

doPlot

Return the log-log scale versus bulk plot with linear fit (default = TRUE).

returnPlot

Return ggplot2 object (default = FALSE)

returnPLAW

Return the power law data (default = FALSE)

returnInfo

Return all the data used in DFA (default = FALSE)

returnLocalScaling

Return estimates of FD for each scale

silent

Silent-ish mode (default = TRUE)

noTitle

Do not generate a title (only the subtitle)

tsName

Name of y added as a subtitle to the plot (default = y)

## Value

The boxcount fractal dimension and the 'local' boxcount fractal dimension

## Note

This function was inspired by the Matlab function boxcount.m written by F. Moisy. Fred Hasselman adapted the function for R for the purpose of the unit square boxcount analysis for 1D time series. The original Matlab toolbox has more options and contains more functions (e.g. 1D and 3D boxcount).

## Examples


fd_boxcount2D(y = rnorm(100))
#>
#>
#> Raterizing time series... Done!
#> Performing 2D boxcount...Done!
#>
#> ~~~o~~o~~casnet~~o~~o~~~
#>
#>  2D boxcount of 1D curve
#>
#>  Full range (n = 9)
#> FD = 1.52
#>
#>  Exclude scales (n = 7)
#> FD = 1.52
#>
#> ~~~o~~o~~casnet~~o~~o~~~

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