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#' Estimate several chaotic invariants using linear regression
#' @description
#' Several chaotic invariants are estimated by using linear regression. This
#' function provides a common interface for the estimate of all these parameters
#' (see \code{\link{corrDim}}, \code{\link{dfa}} and \code{\link{maxLyapunov}}
#' for examples).
#' @param x An object containing all the information needed for the estimate.
#' @param regression.range Range of values on the x-axis on which the regression
#' is performed.
#' @param do.plot Logical value. If TRUE (default value), a plot of the
#' regression is shown.
#' @param ... Additional parameters.
#' @return An estimate of the proper chaotic invariant.
#' @references H. Kantz and T. Schreiber: Nonlinear Time series Analysis
#' (Cambridge university press)
#' @author Constantino A. Garcia
#' @export estimate
estimate = function(x, regression.range, do.plot,...){
UseMethod("estimate")
}
#' Get the embedding dimensions used for compute a chaotic invariant.
#' @param x An object containing all the information needed for the estimate.
#' @return A numeric vector with the embedding dimensions used for compute a
#' chaotic invariant.
#' @references H. Kantz and T. Schreiber: Nonlinear Time series Analysis
#' (Cambridge university press)
#' @author Constantino A. Garcia
#' @export embeddingDims
embeddingDims = function(x){
UseMethod("embeddingDims")
}
embeddingDims.default = function(x){
x$embedding.dims
}
#' Get the radius of the neighborhoods used for the computations of
#' a chaotic invariant.
#' @param x An object containing all the information needed for the estimate of
#' the chaotic invariant.
#' @return A numeric vector with the radius of the neighborhoods used for the
#' computations of a chaotic invariant.
#' @references H. Kantz and T. Schreiber: Nonlinear Time series Analysis
#' (Cambridge university press)
#' @author Constantino A. Garcia
#' @export radius
radius = function(x){
UseMethod("radius")
}
radius.default = function(x){
x$radius
}
#' Get the order of the nonlinear chaotic invariant.
#' @param x An object containing all the information needed for the estimate of
#' the chaotic invariant.
#' @return A numeric vector with the radius of the neighborhoods used for the
#' computations of a chaotic invariant.
#' @seealso \code{\link{corrDim}}, \code{\link{sampleEntropy}}
#' @references H. Kantz and T. Schreiber: Nonlinear Time series Analysis
#' (Cambridge university press)
#' @author Constantino A. Garcia
#' @export nlOrder
nlOrder = function(x){
UseMethod("nlOrder")
}
#' Plot local scaling exponents
#' @description Plots the local scaling exponents of the correlation sum or
#' the average Shannon information (when computing information dimension).
#' @param x An object containing all the information needed for the estimate of
#' the chaotic invariant.
#' @param ... Additional graphical parameters.
#' @references H. Kantz and T. Schreiber: Nonlinear Time series Analysis
#' (Cambridge university press)
#' @author Constantino A. Garcia
#' @export plotLocalScalingExp
plotLocalScalingExp = function(x,...){
UseMethod("plotLocalScalingExp")
}
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