mra.plot {fractalRegression}

Multiscale Regression Plot

Description

A plotting method for constructing scalewise regression plot

Usage

mra.plot(
  betas,
  order = 1,
  ci = FALSE,
  iterations = NULL,
  return.ci = FALSE,
  loess.beta = FALSE,
  loess.ci = FALSE
)

Arguments

betas

an object containing modeling results from multiscale regression analysis. The object should be returned from the mra function of this package.

order

integer representing the detrending order used in the mra calculation. Default is 1.

ci

a logical indicating whether confidence intervals should be computed using the iaafft function from this package. NOTE: with long time series (>> than N = 1,000), this can greatly reduce processing speed. Confidence intervals can be used for conventional significance testing of scale-wise correlation coefficients.

iterations

integer that specifies the the number of surrogate time series to be generated for the purpose of confidence intervals. Default = 19. Larger number of surrogates will slow computational speed but produce better confidence interval estimates.

return.ci

logical indicating whether the confidence intervals should be returned

loess.beta

logical indicating whether a loess fit should be used for displaying multiscale regression coefficient trajectories

loess.ci

logical indicating whether a loess fit should be used to smooth confidence intervals