pompom v0.2.0


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Person-Oriented Method and Perturbation on the Model

An implementation of a hybrid method of person-oriented method and perturbation on the model. Pompom is the initials of the two methods. The hybrid method will provide a multivariate intraindividual variability metric (iRAM). The person-oriented method used in this package refers to uSEM (unified structural equation modeling, see Kim et al., 2007, Gates et al., 2010 and Gates et al., 2012 for details). Perturbation on the model was conducted according to impulse response analysis introduced in Lutkepohl (2007). Kim, J., Zhu, W., Chang, L., Bentler, P. M., & Ernst, T. (2007) <doi:10.1002/hbm.20259>. Gates, K. M., Molenaar, P. C. M., Hillary, F. G., Ram, N., & Rovine, M. J. (2010) <doi:10.1016/j.neuroimage.2009.12.117>. Gates, K. M., & Molenaar, P. C. M. (2012) <doi:10.1016/j.neuroimage.2012.06.026>. Lutkepohl, H. (2007, ISBN:3540262393).



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.

Functions in pompom

Name Description
plot_iRAM_dist Plot distribution of recovery time based on bootstrapped version of iRAM
plot_network_graph Plot the network graph
iRAM_equilibrium Generate iRAM (impulse response anlaysis metric) in the equilibrium form.
plot_integrated_time_profile Plot the time profiles in the integrated form
plot_time_profile Plot time profiles given a time-series generated by impulse response analysis
simts_3node Simulated 3-variate time-series data
parse_beta Parse the beta from model fit object
true_beta_2node The true beta matrix (4 by 4) used in simulation.
model_summary Provide model summary.
bootstrap_iRAM_3node Bootstrapped iRAM (including replications of iRAM and corresponding time profiles) for the 3-variate time-series (simts)
simts_2node Simulated bivariate time-series data
true_beta_3node The true beta matrix (6 by 6) used in simulation.
iRAM Generate iRAM (impulse response anlaysis metric) from model fit.
uSEM Fit a multivariate time series with uSEM (unified Structural Equation Model).
usemmodelfit Model fitbased on similated time-series by uSEM.
bootstrap_iRAM_2node Bootstrapped iRAM (including replications of iRAM and corresponding time profiles) for the bivariate time-series (simts2node)
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Type Package
License GPL-2
Encoding UTF-8
LazyData true
RoxygenNote 6.0.1
VignetteBuilder knitr
NeedsCompilation no
Packaged 2018-07-12 15:05:59 UTC; Xiao Yang
Repository CRAN
Date/Publication 2018-07-13 20:10:03 UTC

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