Person-Oriented Method and Perturbation on the Model - Version 0.2.1 - R包说明

Aug 28, 2026

pompom 是一个用于实现“人导向方法（uSEM）”与“模型扰动（基于脉冲响应分析的 impulse response analysis）”的混合方法 R 包。该包生成多变量个体内变异度指标 iRAM，并提供从模型拟合结果计算 iRAM、iRAM_equilibrium（平衡形式）及其引导法重抽样结果等功能。通过支持不同节点数的引导计算、时间剖面复现与可视化、以及网络图绘制，pompom 可用于时间序列多变量建模与扰动响应分析。

LanguageEnglish

CategoryTechnology

FormatPDF

Pages15

Reading Time38 min

AccessFree to download

Package overview

iRAM

iRAM_equilibrium

bootstrap_iRAM

model and simulation utilities

Package ‘pompom’ May 9, 2026 Type Package Title Person-Oriented Method and Perturbation on the Model Version 0.2.1 Maintainer Xiao Yang <[vwendy@gmail.com](vwendy@gmail.com)> Description 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 model ing, 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) . Gates, K. M., Mole naar, P. C. M., Hillary, F. G., Ram, N., & Rovine, M. J. (2010) . Gates, K. M., & Molenaar, P. C. M. (2012) . Lutkepohl, H. (2007, ISBN:3540262393) . License GPL-2 Encoding UTF-8 LazyData true RoxygenNote 7.1.1 Depends R (>= 3.0.0) Imports lavaan (>= 0.5-23.1097), ggplot2 (>= 2.2.1), reshape2 (>= 1.4.2), qgraph, utils Suggests knitr, rmarkdown, testthat VignetteBuilder knitr NeedsCompilation no Author Xiao Yang [cre, aut], Nilam Ram [aut], Peter Molenaar [aut] Repository CRAN Date/Publication 2021-02-15 00:40:02 UTC Contents bootstrap_iRAM_ 2node .................................. 2 bootstrap_iRAM_ 3node .................................. 3 iRAM ............................................ 4 iRAM_equilibrium ..................................... 5 model_summary ...................................... 6 parse_beta .......................................... 7 plot_integrated_time_profile ................................ 8 plot_iRAM_dist ....................................... 8 plot_network_graph ..................................... 9 plot_time_profile ...................................... 9 simts_ 2node ......................................... 10 simts_ 3node ......................................... 11 true_beta_ 2node ....................................... 11 true_beta_ 3node ....................................... 12 uSEM ............................................ 12 usemmodelfit ........................................ 14 Index 15 | bootstrap_iRAM_ 2node | Bootstrapped iRAM (including replications of iRAM and correspond ing time profiles) for the bivariate time-series (simts2node) | | --- | --- | Description Bootstrapped iRAM (including replications of iRAM and corresponding time profiles) for the bivariate time-series (simts2node) Usage bootstrap_iRAM_ 2node Format An object of class list of length 5 . Details Data bootstrapped from the estimated three-node network structure with 200 replications. bootstrap_iRAM_ 3node 3 Examples bootstrap_iRAM_ 2node$mean \# mean of bootstrapped iRAM bootstrap_iRAM_ 2node$upper \# Upper bound of confidence interval of bootstrapped iRAM bootstrap_iRAM_ 2node$lower \# lower bound of confidence interval of bootstrapped iRAM [bootstrap_iRAM_2node$time.profile.data \# time](bootstrap_iRAM_2node$time.profile.data # time) profiles generated from the bootstrapped beta matrices bootstrap_iRAM_ 2node$recovery .time. reps \# iRAMs generated from the bootstrapped beta matrices | bootstrap_iRAM_ 3node | Bootstrapped iRAM (including replications of iRAM and correspond ing time profiles) for the 3-variate time-series (simts) | | --- | --- | Description Bootstrapped iRAM (including replications of iRAM and corresponding time profiles) for the 3-variate time-series (simts) Usage bootstrap_iRAM_ 3node Format An object of class list of length 5 . Details Data bootstrapped from the estimated three-node network structure with 200 replications. Examples bootstrap_iRAM_ 3node$mean \# mean of bootstrapped iRAM

FAQs

pompom 这个 R 包的核心用途是什么？

pompom 用于实现人导向方法 uSEM 与模型扰动的混合流程，并生成多变量个体内变异度指标 iRAM。

如何从模型拟合结果计算 iRAM？

通过 iRAM() 函数，使用模型拟合对象、beta 矩阵（可为点估计）以及时间序列变量数、滞后阶数、扰动阈值等参数进行计算。

bootstrap_iRAM_2node 和 bootstrap_iRAM_3node 有什么区别？

bootstrap_iRAM_2node 针对二变量时间序列，bootstrap_iRAM_3node 针对三变量时间序列；两者都基于估计的网络结构进行 200 次重抽样，并给出 iRAM 的均值、置信区间上下界以及对应时间剖面数据。

Aug 28, 2026

Upload by Maya Linwood