Ridge maximum likelihood estimation of vector auto-regressive processes and supporting functions for their exploitation. Currently, it includes:
Ridge estimation of the parameters of Vector Auto-Regressive models, commonly referred to as VAR models, through the functions
ridgeVAR1fused. These functions are complemented by
optPenaltyVAR1fused, functions for penalty parameters selection through (leave-one-out) cross-validation (with supporting functions
Functions for simulating VAR-type data (
dataVARX1), data visualization (
plotVAR1data), and some simple data manipulations (
Some diagnostics provided through
Several post-estimation analyses to exploit the fitted model. Among others: support determination of the various VAR model parameters (
sparsifyVARX1), visualization of the (aspects of the) time-series chain graph (
CIGofVAR2), and summary statistics per variate in terms of the VAR(1) model and its associated time-series chain graph (
mutualInfoVAR1). The latter are also available for the VAR(2) and VARX(1) models:
Time-series omics data (
Future versions aim to include more functionality for time-series models.
ragt2ridges-package is a sister-package to the
rags2ridges-package, augmenting the latter 'base' package with functionality for time-course studies. Being its sibling
rags2ridges in the function names (compare e.g.
|License:||GPL (>= 2)|
ragt2ridges includes parts of the
rags2ridges, for it is currently impossible to import this directly.
Wessel N. van Wieringen <[email protected]>
Miok, V., Wilting, S.M., Van Wieringen, W.N. (2017), “Ridge estimation of the VAR(1) model and its time series chain graph from multivariate time-course omics data”, Biometrical Journal, 59(1), 172-191.
Miok, V., Wilting, S.M., Van Wieringen, W.N. (2018), “Ridge estimation of network models from time-course omics data”, Biometrical Journal, <DOI:10.1002/bimj.201700195>.
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