print.pnt: Print objects of class "pnt".

In psychNET: Psychometric Networks for Intensive Longitudinal Data

Description

Generic print function that is used to print information to the console for the function call, the time elapsed, the data used, the fitted model and the model estimates.

Usage

## S3 method for class 'pnt'
print(x, ...)

Arguments

x	: is an object resulted from the psychNET function
...	: Not used

Author(s)

Spyros E. Balafas (author, creator), Sanne Booij, Marco A. Grzegorczyk, Hanneke Wardenaar-Wigman, Ernst C. Wit

Maintainer: Spyros E. Balafas ([e-mail])

References

Lutkepohl, H. (2006). New Introduction to Multiple Time Series Analysis. Springer, New York.

Basu, S., Michailidis, G. (2015). Regularized estimation in sparse high-dimensional time series models. Ann. Statist. 43, no. 4, 1535-1567.

Abegaz, F., Wit, E. (2013). Sparse time series chain graphical models for reconstructing genetic networks. Biostatistics. 14, 3: 586-599.

Haslbeck, J., Waldorp, L. J. (2016). mgm: Structure Estimation for time-varying Mixed Graphical Models in high-dimensional Data.

Nicholson, W. B., Bien, J., Matteson, D. S. (2017). High Dimensional Forecasting via Interpretable Vector Autoregression..

Wilms, I., Basu, S., Bien, J., Matteson D. S. (2017). Sparse Identification and Estimation of High-Dimensional Vector AutoRegressive Moving Averages.

Epskamp, S., Waldorp, L. J., Mottus, R., Borsboom, D. (2016). The Gaussian Graphical Model in Cross-sectional and Time-series Data.

See Also

psychNET

psychNET documentation built on April 14, 2020, 6:39 p.m.