Showing 5 of total 5 results (show query)
vlyubchich
funtimes:Functions for Time Series Analysis
Nonparametric estimators and tests for time series analysis. The functions use bootstrap techniques and robust nonparametric difference-based estimators to test for the presence of possibly non-monotonic trends and for synchronicity of trends in multiple time series.
Maintained by Vyacheslav Lyubchich. Last updated 2 years ago.
7 stars 6.69 score 93 scripts
jmbh
mnet:Modeling Group Differences and Moderation Effects in Statistical Network Models
A toolbox for modeling manifest and latent group differences and moderation effects in various statistical network models.
Maintained by Jonas Haslbeck. Last updated 2 months ago.
4.91 score 18 scripts
xinkaidupsy
IVPP:Invariance Partial Pruning Test
An implementation of the Invariance Partial Pruning (IVPP) approach described in Du, X., Johnson, S. U., Epskamp, S. (2025) The Invariance Partial Pruning Approach to The Network Comparison in Longitudinal Data. IVPP is a two-step method that first test for global network structural difference with invariance test and then inspect specific edge difference with partial pruning.
Maintained by Xinkai Du. Last updated 2 days ago.
3.78 score 7 scripts
williamsandra
GIMMEgVAR:Group Iterative Multiple Model Estimation with 'graphicalVAR'
Data-driven approach for arriving at person-specific time series models from within a Graphical Vector Autoregression (VAR) framework. The method first identifies which relations replicate across the majority of individuals to detect signal from noise. These group-level relations are then used as a foundation for starting the search for person-specific (or individual-level) relations. All estimates are obtained uniquely for each individual in the final models. The method for the 'graphicalVAR' approach is found in Epskamp, Waldorp, Mottus & Borsboom (2018) <doi:10.1080/00273171.2018.1454823>.
Maintained by Sandra Williams Lee. Last updated 11 months ago.
2.70 score
cran
mlVAR:Multi-Level Vector Autoregression
Estimates the multi-level vector autoregression model on time-series data. Three network structures are obtained: temporal networks, contemporaneous networks and between-subjects networks.
Maintained by Sacha Epskamp. Last updated 1 years ago.
2.56 score 2 dependents