# 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).

## Readme

# 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.

## 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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## Vignettes of pompom

Name | ||

Three_node_exmaple.Rmd | ||

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## Last month downloads

## Details

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 |

imports | ggplot2 (>= 2.2.1) , lavaan (>= 0.5-23.1097) , qgraph , reshape2 (>= 1.4.2) , utils |

suggests | knitr , rmarkdown , testthat |

depends | R (>= 3.0.0) |

Contributors | Nilam Ram, Peter Molenaar |

#### Include our badge in your README

```
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```