EmbedDimension: Optimal embedding dimension

EmbedDimensionR Documentation

Optimal embedding dimension

Description

EmbedDimension uses Simplex to evaluate prediction accuracy as a function of embedding dimension.

Usage

EmbedDimension(pathIn = "./", dataFile = "", dataFrame = NULL, pathOut = "", 
  predictFile = "", lib = "", pred = "", maxE = 10, Tp = 1, tau = -1,
  exclusionRadius = 0, columns = "", target = "", embedded = FALSE,
  verbose = FALSE, validLib = vector(), numThreads = 4, showPlot = TRUE)  

Arguments

pathIn

path to dataFile.

dataFile

.csv format data file name. The first column must be a time index or time values. The first row must be column names.

dataFrame

input data.frame. The first column must be a time index or time values. The columns must be named.

pathOut

path for predictFile containing output predictions.

predictFile

output file name.

lib

string with start and stop indices of input data rows used to create the library of observations. A single contiguous range is supported.

pred

string with start and stop indices of input data rows used for predictions. A single contiguous range is supported.

maxE

maximum value of E to evalulate.

Tp

prediction horizon (number of time column rows).

tau

lag of time delay embedding specified as number of time column rows.

exclusionRadius

excludes vectors from the search space of nearest neighbors if their relative time index is within exclusionRadius.

columns

string of whitespace separated column name(s) in the input data used to create the library.

target

column name in the input data used for prediction.

embedded

logical specifying if the input data are embedded.

verbose

logical to produce additional console reporting.

validLib

logical vector the same length as the number of data rows. Any data row represented in this vector as FALSE, will not be included in the library.

numThreads

number of parallel threads for computation.

showPlot

logical to plot results.

Value

A data.frame with columns E, rho.

Examples

data(TentMap)
E.rho = EmbedDimension( dataFrame = TentMap, lib = "1 100", pred = "201 500",
columns = "TentMap", target = "TentMap", showPlot = FALSE )

rEDM documentation built on Aug. 6, 2022, 5:08 p.m.