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pompom

R package to perform time-series analysis and guage the temporal influence from one variable to another.

We created an R package named "pompom" (pompom is the initials of person-oriented modeling and perturbation on the model), and we will use the functions in "pompom" to compute iRAM (impulse response analysis metric) in this pacakge.

iRAM is built upon a hybrid method that combines intraindividual variability methods and network analysis methods in order to model individuals as high-dimensional dynamic systems. This hybrid method is designed and tested to quantify the extent of interaction in a high-dimensional multivariate system, and applicable on experience sampling data.

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Version

Install

install.packages('pompom')

Monthly Downloads

191

Version

0.1.4

License

GPL-2

Maintainer

Xiao Yang

Last Published

January 11th, 2018

Functions in pompom (0.1.4)

parse_beta

Parse the beta from model fit object
plot_iRAM_dist

Plot distribution of recovery time based on bootstrapped version of iRAM
uSEM

Fit a multivariate time series with uSEM (unified Structural Equation Model).
usemmodelfit

Model fitbased on similated time-series by uSEM.
plot_network_graph

Plot the network graph
plot_time_profile

Plot time profiles given a time-series generated by impulse response analysis
bootstrap_iRAM_2node

Bootstrapped iRAM (including replications of iRAM and corresponding time profiles) for the bivariate time-series (simts2node)
bootstrap_iRAM_3node

Bootstrapped iRAM (including replications of iRAM and corresponding time profiles) for the 3-variate time-series (simts)
true_beta_2node

The true beta matrix (4 by 4) used in simulation.
true_beta_3node

The true beta matrix (6 by 6) used in simulation.
iRAM

Generate iRAM (impulse response anlaysis metric) from model fit.
model_summary

Provide model summary.
simts_2node

Simulated bivariate time-series data
simts_3node

Simulated 3-variate time-series data