# Embed: Time-delay Embedding In EGAnet: Exploratory Graph Analysis - A Framework for Estimating the Number of Dimensions in Multivariate Data Using Network Psychometrics

## Description

Reorganizes an individual’s observed time series into an embedded matrix. The embedded matrix is constructed with replicates of an individual time series that are offset from each other in time. The function requires two parameters, one that specifies the number of observations to be used (i.e. the number of embedded dimensions) and the other that specifies the number of observations to offset successive embeddings.

## Usage

 `1` ```Embed(x, E, tau) ```

## Arguments

 `x` Vector. An observed time series to be reorganized into a time-delayed embedded matrix. `E` Integer. Number of embedded dimensions or the number of observations to be used. For example, an `"E = 5"` will generate a matrix with five columns, meaning that five consecutive observations are used to create each row of the embedded matrix. `tau` Integer. Number of observations to offset successive embeddings. A tau of one uses adjacent observations. Default is `"tau = 1"`.

## Value

Returns a matrix containing the embedded matrix.

## Author(s)

Pascal Deboeck <pascal.deboeck at psych.utah.edu>

## References

Deboeck, P. R., Montpetit, M. A., Bergeman, C. S., & Boker, S. M. (2009) Using derivative estimates to describe intraindividual variability at multiple time scales. Psychological Methods, 14, 367-386. doi: 10.1037/a0016622

## Examples

 ```1 2 3``` ```# A time series with 8 time points tseries <- 49:56 embed.tseries <- Embed(tseries, E = 4, tau = 1) ```

EGAnet documentation built on Feb. 17, 2021, 1:06 a.m.