Optimal embedding dimension
EmbedDimension uses Simplex to evaluate
prediction accuracy as a function of embedding dimension.
EmbedDimension(pathIn = "./", dataFile = "", dataFrame = NULL, pathOut = "", predictFile = "", lib = "", pred = "", maxE = 10, Tp = 1, tau = -1, columns = "", target = "", embedded = FALSE, verbose = FALSE, numThreads = 4, showPlot = TRUE)
pathIn |
path to |
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 |
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. |
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. |
numThreads |
number of parallel threads for computation. |
showPlot |
logical to plot results. |
A data.frame with columns E, rho.
data(TentMap) E.rho <- EmbedDimension( dataFrame=TentMap, lib="1 100", pred="201 500", columns="TentMap", target="TentMap", showPlot=FALSE)
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